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BiGo: examining statistical differences in two TE subtypes (repeats and wublastx targets)
Raw
gistfile1.txt
{
"metadata": {
"name": "",
"signature": "sha256:6a2c4937c9f7b56d5a87f63f909673244ddf55041c4a61246dc2d1054b142b7d"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## IPython Notebook for downloading and analyzing data from preprint: \"Indication of family-specific DNA methylation patterns in developing oysters\"\n",
"[http://dx.doi.org/10.1101/012831](http://dx.doi.org/10.1101/012831)\n",
"\n",
"---\n",
"To execute the IPython Notebook in its entirety you will need: \n",
"\n",
"* IPython - [install instructions](http://ipython.org/install.html) \n",
"* BSMAP - [install instructions](https://code.google.com/p/bsmap/) \n",
"* bedtools - [install instructions](https://github.com/arq5x/bedtools2/releases/tag/v2.22.0) \n",
"* R - [install instructions](http://www.r-project.org/) \n",
"* rpy2 (interface to R from Python) - [install instructions](http://rpy.sourceforge.net/) \n",
"\n",
"\n",
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The analysis was originally done on the Mac OSX operating system. \n",
"\n",
"The intent is to download the github repository locally and run so accompaning scripts, etc. are available.\n",
"Detailed Instructions are provided in [GitHub Repo Readme](https://github.com/che625/olson-ms-nb).\n",
"Please note Data files that you will download and will produce are large (>20Gb).\n",
"\n",
"\n",
"The notebook is divided into 5 sections \n",
"\n",
"* [Downloading data](#Downloading-Files) \n",
"\n",
"* [Read aligning: BSMAP](#Running-BSMAP) \n",
"\n",
"* [Global differences: methylkit](#Global-Differences:-methylkit) \n",
"\n",
"* [Differentially methylated loci: methylkit](#Differentially-methylated-loci) \n",
"\n",
"* [Genomic location of DMLs: bedtools](#Genomic-location-of-DMLs) \n",
"\n",
"\n",
"Please post any comments and questions in [issues](https://github.com/che625/olson-ms-nb/issues).\n",
"\n",
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Before getting started, set the location of BSMAP on your computer and hit shift-enter"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"bsmaploc=\"/Users/Shared/Apps/bsmap-2.74/\""
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Downloading Data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#to confirm you current directory run the command and you should see a wd directory\n",
"!ls\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\u001b[31mBiGo_dev.ipynb\u001b[m\u001b[m \u001b[31mREADME.md\u001b[m\u001b[m \u001b[34mscripts\u001b[m\u001b[m \u001b[34mwd\u001b[m\u001b[m\r\n"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cd wd"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"/Users/Steven/Desktop/olson-ms-nb-master/wd\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#This command downloads a archived file including six BS-seq libraries (4.3 Gb)\n",
"\n",
"#!wget http://eagle.fish.washington.edu/trilobite/Crassostrea_gigas_HTSdata/BiGo_lar_fastq_mcf.tgz\n",
"!curl -O http://eagle.fish.washington.edu/trilobite/Crassostrea_gigas_HTSdata/BiGo_lar_fastq_mcf.tgz \n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
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"\r",
" 0 4221M 0 15.3M 0 0 65.4M 0 0:01:04 --:--:-- 0:01:04 66.2M"
]
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" 2 4221M 2 112M 0 0 91.0M 0 0:00:46 0:00:01 0:00:45 91.2M"
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" 4 4221M 4 211M 0 0 94.3M 0 0:00:44 0:00:02 0:00:42 94.4M"
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"\r",
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"\r",
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"\r",
" 10 4221M 10 462M 0 0 88.4M 0 0:00:47 0:00:05 0:00:42 89.5M"
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"\r",
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"\r",
" 14 4221M 14 630M 0 0 87.1M 0 0:00:48 0:00:07 0:00:41 83.8M"
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"\r",
" 16 4221M 16 714M 0 0 86.7M 0 0:00:48 0:00:08 0:00:40 82.5M"
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"\r",
" 18 4221M 18 790M 0 0 85.6M 0 0:00:49 0:00:09 0:00:40 79.0M"
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"\r",
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"\r",
" 28 4221M 28 1194M 0 0 83.4M 0 0:00:50 0:00:14 0:00:36 79.5M"
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" 29 4221M 29 1245M 0 0 81.7M 0 0:00:51 0:00:15 0:00:36 76.1M"
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" 31 4221M 31 1339M 0 0 82.5M 0 0:00:51 0:00:16 0:00:35 79.9M"
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" 34 4221M 34 1442M 0 0 83.6M 0 0:00:50 0:00:17 0:00:33 85.3M"
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"\r",
" 43 4221M 43 1828M 0 0 82.2M 0 0:00:51 0:00:22 0:00:29 77.2M"
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"\r",
" 44 4221M 44 1895M 0 0 81.5M 0 0:00:51 0:00:23 0:00:28 75.4M"
]
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"\r",
" 46 4221M 46 1974M 0 0 81.4M 0 0:00:51 0:00:24 0:00:27 74.4M"
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" 48 4221M 48 2044M 0 0 81.0M 0 0:00:52 0:00:25 0:00:27 72.9M"
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" 52 4221M 52 2208M 0 0 81.0M 0 0:00:52 0:00:27 0:00:25 75.8M"
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"\r",
" 56 4221M 56 2364M 0 0 80.8M 0 0:00:52 0:00:29 0:00:23 78.3M"
]
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"output_type": "stream",
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"text": [
"\r",
" 58 4221M 58 2452M 0 0 81.1M 0 0:00:52 0:00:30 0:00:22 81.5M"
]
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"\r",
" 60 4221M 60 2538M 0 0 81.2M 0 0:00:51 0:00:31 0:00:20 82.0M"
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" 62 4221M 62 2624M 0 0 81.3M 0 0:00:51 0:00:32 0:00:19 83.0M"
]
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"\r",
" 64 4221M 64 2709M 0 0 81.5M 0 0:00:51 0:00:33 0:00:18 85.3M"
]
},
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"output_type": "stream",
"stream": "stdout",
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"\r",
" 66 4221M 66 2794M 0 0 81.6M 0 0:00:51 0:00:34 0:00:17 85.9M"
]
},
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"\r",
" 68 4221M 68 2887M 0 0 81.9M 0 0:00:51 0:00:35 0:00:16 87.0M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 70 4221M 70 2975M 0 0 82.1M 0 0:00:51 0:00:36 0:00:15 87.5M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 72 4221M 72 3065M 0 0 82.3M 0 0:00:51 0:00:37 0:00:14 88.4M"
]
},
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"output_type": "stream",
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"\r",
" 74 4221M 74 3164M 0 0 82.7M 0 0:00:51 0:00:38 0:00:13 90.9M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 77 4221M 77 3258M 0 0 83.0M 0 0:00:50 0:00:39 0:00:11 92.8M"
]
},
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"\r",
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]
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"output_type": "stream",
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"\r",
" 81 4221M 81 3440M 0 0 83.4M 0 0:00:50 0:00:41 0:00:09 92.8M"
]
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"output_type": "stream",
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"\r",
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]
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"\r",
" 85 4221M 85 3629M 0 0 83.9M 0 0:00:50 0:00:43 0:00:07 92.9M"
]
},
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"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 88 4221M 88 3716M 0 0 84.0M 0 0:00:50 0:00:44 0:00:06 91.6M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 90 4221M 90 3810M 0 0 84.2M 0 0:00:50 0:00:45 0:00:05 91.6M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 91 4221M 91 3879M 0 0 83.9M 0 0:00:50 0:00:46 0:00:04 87.9M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 93 4221M 93 3960M 0 0 83.8M 0 0:00:50 0:00:47 0:00:03 84.8M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 95 4221M 95 4039M 0 0 83.7M 0 0:00:50 0:00:48 0:00:02 82.0M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 98 4221M 98 4138M 0 0 84.0M 0 0:00:50 0:00:49 0:00:01 84.2M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 4221M 100 4221M 0 0 84.2M 0 0:00:50 0:00:50 --:--:-- 85.0M\r\n"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#uncompress files\n",
"!tar -zxvf BiGo_lar_fastq_mcf.tgz"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"x mcf_M1_R1.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_M1_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_M3_R1.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_M3_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T1D3_R1.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T1D3_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T1D5_R1.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T1D5_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T3D3_R1.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T3D3_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T3D5_R1.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"x mcf_T3D5_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#remove BiGo_lar_fastq_mcf.tgz\n",
"#!rm BiGo_lar_fastq_mcf.tgz "
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Downloading the oyster genome \n",
"#!wget http://eagle.fish.washington.edu/trilobite/Crassostrea_gigas_ensembl_tracks/Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa\n",
"!curl -O http://eagle.fish.washington.edu/trilobite/Crassostrea_gigas_ensembl_tracks/Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \n",
" "
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 13 541M 13 72.1M 0 0 92.9M 0 0:00:05 --:--:-- 0:00:05 93.1M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 32 541M 32 177M 0 0 99.7M 0 0:00:05 0:00:01 0:00:04 99.8M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 50 541M 50 273M 0 0 98.5M 0 0:00:05 0:00:02 0:00:03 98.6M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 69 541M 69 375M 0 0 99.4M 0 0:00:05 0:00:03 0:00:02 99.5M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 86 541M 86 469M 0 0 98.3M 0 0:00:05 0:00:04 0:00:01 98.3M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 541M 100 541M 0 0 99.1M 0 0:00:05 0:00:05 --:--:-- 100M\r\n"
]
}
],
"prompt_number": 6
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Running BSMAP"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#bsmap will need to be downloaded if not already installed from https://code.google.com/p/bsmap/\n",
"#another option in running bsmap on iPlant (iplantcollaborative.org)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"M1\",\"T1D3\",\"T1D5\", \"M3\", \"T3D3\", \"T3D5\"):\n",
" !{bsmaploc}bsmap \\\n",
"-a mcf_{i}_R1.fastq \\\n",
"-b mcf_{i}_R2.fastq \\\n",
"-d Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \\\n",
"-o bsmap_out_{i}.sam \\\n",
"-p 8"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"BSMAP v2.74\r\n",
"Start at: Fri Jan 30 11:44:33 2015\r\n",
"\r\n",
"Input reference file: Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" \t(format: FASTA)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Load in 7658 db seqs, total size 557717710 bp. 9 secs passed\r\n",
"total_kmers: 43046721\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Create seed table. 24 secs passed\r\n",
"max number of mismatches: read_length * 8% \tmax gap size: 0\r\n",
"kmer cut-off ratio: 5e-07\r\n",
"max multi-hits: 100\tmax Ns: 5\tseed size: 16\tindex interval: 4\r\n",
"quality cutoff: 0\tbase quality char: '!'\r\n",
"min fragment size:28\tmax fragemt size:500\r\n",
"start from read #1\tend at read #4294967295\r\n",
"additional alignment: T in reads => C in reference\r\n",
"mapping strand (read_1): ++,-+\r\n",
"mapping strand (read_2): +-,--\r\n",
"Pair-end alignment(8 threads)\r\n",
"Input read file #1: mcf_M1_R1.fastq \t(format: FASTQ)\r\n",
"Input read file #2: mcf_M1_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" \t(format: FASTQ)\r\n",
"Output file: bsmap_out_M1.sam\t (format: SAM)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t50000 read pairs finished. 74 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t100000 read pairs finished. 75 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t150000 read pairs finished. 77 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t250000 read pairs finished. 78 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t300000 read pairs finished. 79 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t200000 read pairs finished. 79 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t350000 read pairs finished. 80 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t400000 read pairs finished. 80 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t450000 read pairs finished. 127 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t500000 read pairs finished. 128 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t550000 read pairs finished. 131 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t600000 read pairs finished. 131 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t650000 read pairs finished. 132 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t700000 read pairs finished. 133 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t750000 read pairs finished. 134 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t800000 read pairs finished. 135 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t850000 read pairs finished. 180 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t900000 read pairs finished. 181 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1000000 read pairs finished. 184 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t1050000 read pairs finished. 185 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t950000 read pairs finished. 185 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t1100000 read pairs finished. 187 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t1150000 read pairs finished. 188 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1200000 read pairs finished. 188 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1250000 read pairs finished. 233 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t1300000 read pairs finished. 234 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1350000 read pairs finished. 237 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t1400000 read pairs finished. 238 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1450000 read pairs finished. 239 secs passed\r\n"
]
},
{
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"text": [
"Thread #5: \t1500000 read pairs finished. 241 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t1550000 read pairs finished. 243 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1600000 read pairs finished. 244 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t1700000 read pairs finished. 289 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1650000 read pairs finished. 290 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1750000 read pairs finished. 292 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t1800000 read pairs finished. 294 secs passed\r\n"
]
},
{
"output_type": "stream",
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"text": [
"Thread #1: \t1850000 read pairs finished. 295 secs passed\r\n"
]
},
{
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"Thread #5: \t1900000 read pairs finished. 298 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t1950000 read pairs finished. 299 secs passed\r\n"
]
},
{
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"text": [
"Thread #6: \t2000000 read pairs finished. 300 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t2050000 read pairs finished. 345 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t2100000 read pairs finished. 346 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t2150000 read pairs finished. 347 secs passed\r\n"
]
},
{
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"Thread #7: \t2200000 read pairs finished. 349 secs passed\r\n"
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},
{
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"Thread #1: \t2250000 read pairs finished. 352 secs passed\r\n"
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},
{
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"Thread #5: \t2300000 read pairs finished. 354 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t2350000 read pairs finished. 355 secs passed\r\n"
]
},
{
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"text": [
"Thread #6: \t2400000 read pairs finished. 356 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t2450000 read pairs finished. 407 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t2500000 read pairs finished. 408 secs passed\r\n"
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{
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"Thread #0: \t2550000 read pairs finished. 408 secs passed\r\n"
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},
{
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"Thread #7: \t2600000 read pairs finished. 410 secs passed\r\n"
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},
{
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"Thread #1: \t2650000 read pairs finished. 416 secs passed\r\n"
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},
{
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"text": [
"Thread #5: \t2700000 read pairs finished. 421 secs passed\r\n"
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},
{
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{
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},
{
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"Thread #2: \t2850000 read pairs finished. 473 secs passed\r\n"
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},
{
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{
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{
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},
{
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"text": [
"Thread #1: \t3050000 read pairs finished. 480 secs passed\r\n"
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},
{
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"text": [
"Thread #5: \t3100000 read pairs finished. 485 secs passed\r\n"
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},
{
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"text": [
"Thread #6: \t3150000 read pairs finished. 486 secs passed\r\n"
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},
{
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"text": [
"Thread #4: \t3200000 read pairs finished. 486 secs passed\r\n"
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},
{
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{
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{
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"Thread #5: \t3500000 read pairs finished. 544 secs passed\r\n"
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{
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{
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},
{
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"text": [
"Thread #0: \t3700000 read pairs finished. 592 secs passed\r\n"
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},
{
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"Thread #3: \t3750000 read pairs finished. 592 secs passed\r\n"
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},
{
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{
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"text": [
"Thread #2: \t3650000 read pairs finished. 593 secs passed\r\n"
]
},
{
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"Thread #1: \t3850000 read pairs finished. 596 secs passed\r\n"
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{
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},
{
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},
{
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{
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"Thread #3: \t4100000 read pairs finished. 648 secs passed\r\n"
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{
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{
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},
{
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{
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},
{
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{
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{
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},
{
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},
{
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{
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"text": [
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{
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{
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{
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},
{
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"Thread #0: \t6050000 read pairs finished. 915 secs passed\r\n"
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},
{
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"text": [
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},
{
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{
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{
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{
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{
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{
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},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t7000000 read pairs finished. 1033 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7050000 read pairs finished. 1042 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t7100000 read pairs finished. 1047 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t7150000 read pairs finished. 1049 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t7200000 read pairs finished. 1056 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t7250000 read pairs finished. 1078 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t7300000 read pairs finished. 1087 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t7350000 read pairs finished. 1088 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t7400000 read pairs finished. 1089 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7450000 read pairs finished. 1098 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t7500000 read pairs finished. 1103 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t7550000 read pairs finished. 1104 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t7600000 read pairs finished. 1111 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t7650000 read pairs finished. 1132 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t7700000 read pairs finished. 1141 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t7750000 read pairs finished. 1142 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t7800000 read pairs finished. 1143 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7850000 read pairs finished. 1147 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t8023643 read pairs finished. 1148 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t7900000 read pairs finished. 1149 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t7950000 read pairs finished. 1149 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t8000000 read pairs finished. 1150 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total number of aligned reads: \r\n",
"pairs: 3982551 (50%)\r\n",
"single a: 1489442 (19%)\r\n",
"single b: 1430646 (18%)\r\n",
"Done.\r\n",
"Finished at Fri Jan 30 12:03:43 2015\r\n",
"Total time consumed: 1150 secs\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"BSMAP v2.74\r\n",
"Start at: Fri Jan 30 12:03:44 2015\r\n",
"\r\n",
"Input reference file: Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" \t(format: FASTA)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Load in 7658 db seqs, total size 557717710 bp. 9 secs passed\r\n",
"total_kmers: 43046721\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Create seed table. 25 secs passed\r\n",
"max number of mismatches: read_length * 8% \tmax gap size: 0\r\n",
"kmer cut-off ratio: 5e-07\r\n",
"max multi-hits: 100\tmax Ns: 5\tseed size: 16\tindex interval: 4\r\n",
"quality cutoff: 0\tbase quality char: '!'\r\n",
"min fragment size:28\tmax fragemt size:500\r\n",
"start from read #1\tend at read #4294967295\r\n",
"additional alignment: T in reads => C in reference\r\n",
"mapping strand (read_1): ++,-+\r\n",
"mapping strand (read_2): +-,--\r\n",
"Pair-end alignment(8 threads)\r\n",
"Input read file #1: mcf_T1D3_R1.fastq \t(format: FASTQ)\r\n",
"Input read file #2: mcf_T1D3_R2.fastq \t(format: FASTQ)\r\n",
"Output file: bsmap_out_T1D3.sam\t (format: SAM)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t50000 read pairs finished. 75 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t100000 read pairs finished. 76 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t150000 read pairs finished. 77 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t200000 read pairs finished. 78 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t250000 read pairs finished. 78 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t300000 read pairs finished. 79 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t350000 read pairs finished. 79 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t400000 read pairs finished. 81 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t450000 read pairs finished. 128 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t500000 read pairs finished. 129 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t550000 read pairs finished. 129 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t600000 read pairs finished. 130 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t650000 read pairs finished. 131 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t700000 read pairs finished. 132 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t750000 read pairs finished. 133 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t800000 read pairs finished. 134 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t850000 read pairs finished. 181 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t900000 read pairs finished. 182 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t950000 read pairs finished. 182 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1000000 read pairs finished. 183 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1050000 read pairs finished. 183 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1100000 read pairs finished. 185 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t1150000 read pairs finished. 185 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t1200000 read pairs finished. 187 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1250000 read pairs finished. 234 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t1300000 read pairs finished. 235 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t1350000 read pairs finished. 235 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1400000 read pairs finished. 236 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1450000 read pairs finished. 236 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #5: \t1550000 read pairs finished. 238 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1500000 read pairs finished. 238 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t1600000 read pairs finished. 240 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1650000 read pairs finished. 286 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t1700000 read pairs finished. 288 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t1750000 read pairs finished. 288 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1800000 read pairs finished. 288 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1850000 read pairs finished. 289 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t1900000 read pairs finished. 290 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1950000 read pairs finished. 290 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t2000000 read pairs finished. 292 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t2050000 read pairs finished. 339 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t2200000 read pairs finished. 340 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #2: \t2150000 read pairs finished. 340 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t2100000 read pairs finished. 340 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t2250000 read pairs finished. 341 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #5: \t2300000 read pairs finished. 341 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t2350000 read pairs finished. 341 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #7: \t2400000 read pairs finished. 342 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t2450000 read pairs finished. 383 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #6: \t2500000 read pairs finished. 389 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t2550000 read pairs finished. 390 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t2600000 read pairs finished. 392 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t2700000 read pairs finished. 392 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t2650000 read pairs finished. 392 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t2750000 read pairs finished. 393 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t2800000 read pairs finished. 393 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t2850000 read pairs finished. 433 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t2900000 read pairs finished. 439 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t2950000 read pairs finished. 442 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t3100000 read pairs finished. 444 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t3050000 read pairs finished. 444 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t3000000 read pairs finished. 445 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t3150000 read pairs finished. 445 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t3200000 read pairs finished. 445 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t3250000 read pairs finished. 482 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t3300000 read pairs finished. 488 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t3350000 read pairs finished. 491 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t3400000 read pairs finished. 494 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t3450000 read pairs finished. 496 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t3550000 read pairs finished. 499 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t3500000 read pairs finished. 499 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t3600000 read pairs finished. 499 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t3650000 read pairs finished. 535 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t3700000 read pairs finished. 539 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t3750000 read pairs finished. 541 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t3800000 read pairs finished. 544 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t3850000 read pairs finished. 547 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t3900000 read pairs finished. 550 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t3950000 read pairs finished. 550 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t4000000 read pairs finished. 553 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t4050000 read pairs finished. 590 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t4100000 read pairs finished. 592 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t4150000 read pairs finished. 594 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t4200000 read pairs finished. 596 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t4250000 read pairs finished. 598 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t4300000 read pairs finished. 600 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t4350000 read pairs finished. 600 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t4400000 read pairs finished. 604 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t4450000 read pairs finished. 640 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t4500000 read pairs finished. 644 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t4550000 read pairs finished. 648 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t4600000 read pairs finished. 649 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t4650000 read pairs finished. 649 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t4700000 read pairs finished. 651 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t4750000 read pairs finished. 652 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t4800000 read pairs finished. 654 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t5016400 read pairs finished. 659 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t4850000 read pairs finished. 667 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t4900000 read pairs finished. 668 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t4950000 read pairs finished. 668 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t5000000 read pairs finished. 669 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total number of aligned reads: \r\n",
"pairs: 2717832 (54%)\r\n",
"single a: 1117376 (22%)\r\n",
"single b: 1178712 (23%)\r\n",
"Done.\r\n",
"Finished at Fri Jan 30 12:14:53 2015\r\n",
"Total time consumed: 669 secs\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"BSMAP v2.74\r\n",
"Start at: Fri Jan 30 12:14:54 2015\r\n",
"\r\n",
"Input reference file: Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \t(format: FASTA)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Load in 7658 db seqs, total size 557717710 bp. 9 secs passed\r\n",
"total_kmers: 43046721\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Create seed table. 26 secs passed\r\n",
"max number of mismatches: read_length * 8% \tmax gap size: 0\r\n",
"kmer cut-off ratio: 5e-07\r\n",
"max multi-hits: 100\tmax Ns: 5\tseed size: 16\tindex interval: 4\r\n",
"quality cutoff: 0\tbase quality char: '!'\r\n",
"min fragment size:28\tmax fragemt size:500\r\n",
"start from read #1\tend at read #4294967295\r\n",
"additional alignment: T in reads => C in reference\r\n",
"mapping strand (read_1): ++,-+\r\n",
"mapping strand (read_2): +-,--\r\n",
"Pair-end alignment(8 threads)\r\n",
"Input read file #1: mcf_T1D5_R1.fastq \t(format: FASTQ)\r\n",
"Input read file #2: mcf_T1D5_R2.fastq \t(format: FASTQ)\r\n",
"Output file: bsmap_out_T1D5.sam\t (format: SAM)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t50000 read pairs finished. 78 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t100000 read pairs finished. 80 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t150000 read pairs finished. 80 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t200000 read pairs finished. 81 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t250000 read pairs finished. 82 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t300000 read pairs finished. 82 secs passed\r\n"
]
},
{
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"text": [
"Thread #6: \t350000 read pairs finished. 83 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t400000 read pairs finished. 83 secs passed\r\n"
]
},
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"Thread #5: \t450000 read pairs finished. 133 secs passed\r\n"
]
},
{
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"Thread #0: \t500000 read pairs finished. 135 secs passed\r\n"
]
},
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"text": [
"Thread #3: \t550000 read pairs finished. 135 secs passed\r\n"
]
},
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"text": [
"Thread #4: \t600000 read pairs finished. 136 secs passed\r\n"
]
},
{
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"Thread #1: \t650000 read pairs finished. 137 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t700000 read pairs finished. 138 secs passed\r\n"
]
},
{
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"Thread #6: \t750000 read pairs finished. 138 secs passed\r\n"
]
},
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"Thread #7: \t800000 read pairs finished. 139 secs passed\r\n"
]
},
{
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"Thread #5: \t850000 read pairs finished. 189 secs passed\r\n"
]
},
{
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"Thread #0: \t900000 read pairs finished. 190 secs passed\r\n"
]
},
{
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"Thread #3: \t950000 read pairs finished. 190 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t1000000 read pairs finished. 192 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t1050000 read pairs finished. 192 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t1100000 read pairs finished. 192 secs passed\r\n"
]
},
{
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"Thread #6: \t1150000 read pairs finished. 193 secs passed\r\n"
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"Thread #7: \t1200000 read pairs finished. 195 secs passed\r\n"
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{
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"Thread #5: \t1250000 read pairs finished. 243 secs passed\r\n"
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{
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"Thread #0: \t1300000 read pairs finished. 245 secs passed\r\n"
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"Thread #3: \t1350000 read pairs finished. 246 secs passed\r\n"
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"Thread #4: \t1400000 read pairs finished. 247 secs passed\r\n"
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{
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"Thread #1: \t1450000 read pairs finished. 247 secs passed\r\n"
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{
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"Thread #2: \t1500000 read pairs finished. 248 secs passed\r\n"
]
},
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"Thread #6: \t1550000 read pairs finished. 248 secs passed\r\n"
]
},
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"Thread #7: \t1600000 read pairs finished. 249 secs passed\r\n"
]
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{
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"Thread #5: \t1650000 read pairs finished. 297 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t1700000 read pairs finished. 299 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t1750000 read pairs finished. 300 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t1800000 read pairs finished. 302 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t1850000 read pairs finished. 304 secs passed\r\n"
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{
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"text": [
"Thread #2: \t1900000 read pairs finished. 304 secs passed\r\n"
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{
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"Thread #6: \t1950000 read pairs finished. 304 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t2000000 read pairs finished. 305 secs passed\r\n"
]
},
{
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"text": [
"Thread #5: \t2050000 read pairs finished. 352 secs passed\r\n"
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{
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"Thread #0: \t2100000 read pairs finished. 353 secs passed\r\n"
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{
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"Thread #3: \t2150000 read pairs finished. 354 secs passed\r\n"
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"text": [
"Thread #4: \t2200000 read pairs finished. 357 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t2250000 read pairs finished. 358 secs passed\r\n"
]
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{
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"text": [
"Thread #2: \t2300000 read pairs finished. 360 secs passed\r\n"
]
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{
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"text": [
"Thread #6: \t2350000 read pairs finished. 360 secs passed\r\n"
]
},
{
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"Thread #7: \t2400000 read pairs finished. 361 secs passed\r\n"
]
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"text": [
"Thread #5: \t2450000 read pairs finished. 407 secs passed\r\n"
]
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{
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"text": [
"Thread #0: \t2500000 read pairs finished. 408 secs passed\r\n"
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"Thread #1: \t2650000 read pairs finished. 414 secs passed\r\n"
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{
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"Thread #2: \t2700000 read pairs finished. 415 secs passed\r\n"
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{
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"Thread #6: \t2750000 read pairs finished. 416 secs passed\r\n"
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"Thread #5: \t2850000 read pairs finished. 462 secs passed\r\n"
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{
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"Thread #3: \t2950000 read pairs finished. 464 secs passed\r\n"
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"Thread #4: \t3000000 read pairs finished. 468 secs passed\r\n"
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{
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"Thread #1: \t3050000 read pairs finished. 469 secs passed\r\n"
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"text": [
"Thread #2: \t3100000 read pairs finished. 471 secs passed\r\n"
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"Thread #6: \t3150000 read pairs finished. 471 secs passed\r\n"
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"Thread #2: \t3500000 read pairs finished. 525 secs passed\r\n"
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"Thread #6: \t3550000 read pairs finished. 528 secs passed\r\n"
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"Thread #7: \t3600000 read pairs finished. 529 secs passed\r\n"
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"Thread #5: \t3650000 read pairs finished. 572 secs passed\r\n"
]
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{
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"Thread #0: \t3700000 read pairs finished. 574 secs passed\r\n"
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{
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"Thread #3: \t3750000 read pairs finished. 574 secs passed\r\n"
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{
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"text": [
"Thread #4: \t3800000 read pairs finished. 577 secs passed\r\n"
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"Thread #1: \t3850000 read pairs finished. 578 secs passed\r\n"
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"Thread #7: \t4000000 read pairs finished. 590 secs passed\r\n"
]
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{
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"Thread #0: \t4100000 read pairs finished. 630 secs passed\r\n"
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{
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"Thread #3: \t4150000 read pairs finished. 630 secs passed\r\n"
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"Thread #5: \t4050000 read pairs finished. 630 secs passed\r\n"
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"Thread #4: \t4200000 read pairs finished. 631 secs passed\r\n"
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"Thread #2: \t4300000 read pairs finished. 632 secs passed\r\n"
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"Thread #4: \t4600000 read pairs finished. 686 secs passed\r\n"
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"Thread #6: \t4750000 read pairs finished. 687 secs passed\r\n"
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"Thread #2: \t5050000 read pairs finished. 742 secs passed\r\n"
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"Thread #6: \t5150000 read pairs finished. 742 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t5100000 read pairs finished. 742 secs passed\r\n"
]
},
{
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"Thread #7: \t5200000 read pairs finished. 747 secs passed\r\n"
]
},
{
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"Thread #2: \t5450000 read pairs finished. 797 secs passed\r\n"
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"Thread #6: \t5500000 read pairs finished. 797 secs passed\r\n"
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{
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"Thread #4: \t5400000 read pairs finished. 798 secs passed\r\n"
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"Thread #5: \t5350000 read pairs finished. 798 secs passed\r\n"
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{
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"text": [
"Thread #1: \t5550000 read pairs finished. 799 secs passed\r\n"
]
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{
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"Thread #7: \t5600000 read pairs finished. 800 secs passed\r\n"
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},
{
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"text": [
"Thread #0: \t5650000 read pairs finished. 842 secs passed\r\n"
]
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{
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"Thread #3: \t5700000 read pairs finished. 846 secs passed\r\n"
]
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{
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"text": [
"Thread #2: \t5750000 read pairs finished. 851 secs passed\r\n"
]
},
{
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"Thread #6: \t5800000 read pairs finished. 853 secs passed\r\n"
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{
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"Thread #4: \t5850000 read pairs finished. 853 secs passed\r\n"
]
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{
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"Thread #5: \t5900000 read pairs finished. 854 secs passed\r\n"
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{
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"text": [
"Thread #1: \t5950000 read pairs finished. 855 secs passed\r\n"
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},
{
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"Thread #7: \t6000000 read pairs finished. 855 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #6: \t6179274 read pairs finished. 864 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t6050000 read pairs finished. 867 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t6100000 read pairs finished. 868 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t6150000 read pairs finished. 869 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total number of aligned reads: \r\n",
"pairs: 2725017 (44%)\r\n",
"single a: 1704213 (28%)\r\n",
"single b: 1415455 (23%)\r\n",
"Done.\r\n",
"Finished at Fri Jan 30 12:29:23 2015\r\n",
"Total time consumed: 869 secs\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"BSMAP v2.74\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Start at: Fri Jan 30 12:29:24 2015\r\n",
"\r\n",
"Input reference file: Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \t(format: FASTA)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Load in 7658 db seqs, total size 557717710 bp. 9 secs passed\r\n",
"total_kmers: 43046721\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Create seed table. 26 secs passed\r\n",
"max number of mismatches: read_length * 8% \tmax gap size: 0\r\n",
"kmer cut-off ratio: 5e-07\r\n",
"max multi-hits: 100\tmax Ns: 5\tseed size: 16\tindex interval: 4\r\n",
"quality cutoff: 0\tbase quality char: '!'\r\n",
"min fragment size:28\tmax fragemt size:500\r\n",
"start from read #1\tend at read #4294967295\r\n",
"additional alignment: T in reads => C in reference\r\n",
"mapping strand (read_1): ++,-+\r\n",
"mapping strand (read_2): +-,--\r\n",
"Pair-end alignment(8 threads)\r\n",
"Input read file #1: mcf_M3_R1.fastq \t(format: FASTQ)\r\n",
"Input read file #2: mcf_M3_R2.fastq"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" \t(format: FASTQ)\r\n",
"Output file: bsmap_out_M3.sam\t (format: SAM)\r\n"
]
},
{
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"Thread #"
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"Thread #5: \t7050000 read pairs finished. 995 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
": \t7100000 read pairs finished. 996 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t7150000 read pairs finished. 999 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t7200000 read pairs finished. 1000 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7250000 read pairs finished. 1028 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t7300000 read pairs finished. 1041 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t7350000 read pairs finished. 1045 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t7400000 read pairs finished. 1047 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t7450000 read pairs finished. 1048 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t7500000 read pairs finished. 1048 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"2: \t7550000 read pairs finished. 1051 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t7600000 read pairs finished. 1052 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t7867124 read pairs finished. 1061 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7650000 read pairs finished. 1068 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t7700000 read pairs finished. 1072 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t7750000 read pairs finished. 1073 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t7800000 read pairs finished. 1073 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t7850000 read pairs finished. 1073 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total number of aligned reads: \r\n",
"pairs: 4545286 (58%)\r\n",
"single a: 1331428 (17%)\r\n",
"single b: 1233409 (16%)\r\n",
"Done.\r\n",
"Finished at Fri Jan 30 12:47:17 2015\r\n",
"Total time consumed: 1073 secs\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"BSMAP v2.74\r\n",
"Start at: Fri Jan 30 12:47:18 2015\r\n",
"\r\n",
"Input reference file: Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \t(format: FASTA)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Load in 7658 db seqs, total size 557717710 bp. 9 secs passed\r\n",
"total_kmers: 43046721\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Create seed table. 27 secs passed\r\n",
"max number of mismatches: read_length * 8% \tmax gap size: 0\r\n",
"kmer cut-off ratio: 5e-07\r\n",
"max multi-hits: 100\tmax Ns: 5\tseed size: 16\tindex interval: 4\r\n",
"quality cutoff: 0\tbase quality char: '!'\r\n",
"min fragment size:28\tmax fragemt size:500\r\n",
"start from read #1\tend at read #4294967295\r\n",
"additional alignment: T in reads => C in reference\r\n",
"mapping strand (read_1): ++,-+\r\n",
"mapping strand (read_2): +-,--\r\n",
"Pair-end alignment(8 threads)\r\n",
"Input read file #1: mcf_T3D3_R1.fastq \t(format: FASTQ)\r\n",
"Input read file #2: mcf_T3D3_R2.fastq \t(format: FASTQ)\r\n",
"Output file: bsmap_out_T3D3.sam\t (format: SAM)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t50000 read pairs finished. 77 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t100000 read pairs finished. 78 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t150000 read pairs finished. 79 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t200000 read pairs finished. 80 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t250000 read pairs finished. 80 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t300000 read pairs finished. 82 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t400000 read pairs finished. 82 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t350000 read pairs finished. 83 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t450000 read pairs finished. 130 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t500000 read pairs finished. 131 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t550000 read pairs finished. 132 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t600000 read pairs finished. 133 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t650000 read pairs finished. 134 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t700000 read pairs finished. 135 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t750000 read pairs finished. 136 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t800000 read pairs finished. 138 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t850000 read pairs finished. 183 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t900000 read pairs finished. 184 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t950000 read pairs finished. 186 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1000000 read pairs finished. 186 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t1050000 read pairs finished. 187 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1100000 read pairs finished. 189 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t1150000 read pairs finished. 190 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1200000 read pairs finished. 193 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1250000 read pairs finished. 236 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t1300000 read pairs finished. 237 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t1350000 read pairs finished. 238 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1400000 read pairs finished. 239 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t1450000 read pairs finished. 239 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1500000 read pairs finished. 245 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t1550000 read pairs finished. 246 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t1600000 read pairs finished. 248 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t1650000 read pairs finished. 289 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t1700000 read pairs finished. 290 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t1750000 read pairs finished. 292 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t1800000 read pairs finished. 293 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t1850000 read pairs finished. 293 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t1900000 read pairs finished. 297 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t1950000 read pairs finished. 298 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t2000000 read pairs finished. 302 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t2050000 read pairs finished. 342 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t2100000 read pairs finished. 343 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t2150000 read pairs finished. 345 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t2200000 read pairs finished. 346 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t2250000 read pairs finished. 346 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t2300000 read pairs finished. 349 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #7: \t2350000 read pairs finished. 351 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #0: \t2400000 read pairs finished. 358 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #5: \t2650000 read pairs finished. 398 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #6: \t2600000 read pairs finished. 399 secs passed\r\n"
]
},
{
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"text": [
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]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t2500000 read pairs finished. 400 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t2700000 read pairs finished. 400 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #3: \t2450000 read pairs finished. 401 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t2750000 read pairs finished. 402 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t2800000 read pairs finished. 411 secs passed\r\n"
]
},
{
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"text": [
"Thread #5: \t2850000 read pairs finished. 451 secs passed\r\n"
]
},
{
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"text": [
"Thread #6: \t2900000 read pairs finished. 452 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t2950000 read pairs finished. 453 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #4: \t3000000 read pairs finished. 453 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t3050000 read pairs finished. 453 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t3100000 read pairs finished. 454 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t3150000 read pairs finished. 455 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t3200000 read pairs finished. 465 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #5: \t3250000 read pairs finished. 502 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t3300000 read pairs finished. 506 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #4: \t3400000 read pairs finished. 506 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t3350000 read pairs finished. 507 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t3450000 read pairs finished. 507 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t3500000 read pairs finished. 508 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t3550000 read pairs finished. 508 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t3600000 read pairs finished. 518 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t3650000 read pairs finished. 554 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t3700000 read pairs finished. 558 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t3750000 read pairs finished. 559 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t3800000 read pairs finished. 559 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t3850000 read pairs finished. 560 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t3900000 read pairs finished. 561 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t3950000 read pairs finished. 562 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t4000000 read pairs finished. 573 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t4050000 read pairs finished. 607 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t4100000 read pairs finished. 610 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #4: \t4150000 read pairs finished. 610 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t4200000 read pairs finished. 611 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t4250000 read pairs finished. 615 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t4300000 read pairs finished. 616 secs passed\r\n"
]
},
{
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]
},
{
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"text": [
"Thread #0: \t4400000 read pairs finished. 628 secs passed\r\n"
]
},
{
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"Thread #5: \t4450000 read pairs finished. 660 secs passed\r\n"
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},
{
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"Thread #6: \t4500000 read pairs finished. 663 secs passed\r\n"
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},
{
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"Thread #4: \t4550000 read pairs finished. 664 secs passed\r\n"
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{
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"text": [
"Thread #2: \t4600000 read pairs finished. 665 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t4650000 read pairs finished. 669 secs passed\r\n"
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},
{
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"Thread #3: \t4700000 read pairs finished. 669 secs passed\r\n"
]
},
{
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"text": [
"Thread #7: \t4750000 read pairs finished. 670 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t4800000 read pairs finished. 682 secs passed\r\n"
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},
{
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"Thread #5: \t4850000 read pairs finished. 713 secs passed\r\n"
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},
{
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"text": [
"Thread #6: \t4900000 read pairs finished. 716 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t4950000 read pairs finished. 716 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t5000000 read pairs finished. 718 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t5050000 read pairs finished. 721 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t5100000 read pairs finished. 722 secs passed\r\n"
]
},
{
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"Thread #7: \t5150000 read pairs finished. 723 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t5200000 read pairs finished. 736 secs passed\r\n"
]
},
{
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"text": [
"Thread #2: \t5400000 read pairs finished. 771 secs passed\r\n"
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},
{
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"Thread #4: \t5350000 read pairs finished. 772 secs passed\r\n"
]
},
{
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"Thread #5: \t5250000 read pairs finished. 773 secs passed\r\n"
]
},
{
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"Thread #6: \t5300000 read pairs finished. 773 secs passed\r\n"
]
},
{
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"Thread #1: \t5450000 read pairs finished. 774 secs passed\r\n"
]
},
{
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"text": [
"Thread #3: \t5500000 read pairs finished. 774 secs passed\r\n"
]
},
{
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]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t5600000 read pairs finished. 787 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #2: \t5650000 read pairs finished. 824 secs passed\r\n"
]
},
{
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"Thread #4: \t5700000 read pairs finished. 824 secs passed\r\n"
]
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{
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"Thread #5: \t5750000 read pairs finished. 825 secs passed\r\n"
]
},
{
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"Thread #6: \t5800000 read pairs finished. 826 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t5850000 read pairs finished. 827 secs passed\r\n"
]
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{
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"Thread #3: \t5900000 read pairs finished. 828 secs passed\r\n"
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{
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"Thread #7: \t5950000 read pairs finished. 828 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t6000000 read pairs finished. 841 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t6100000 read pairs finished. 877 secs passed\r\n"
]
},
{
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"Thread #2: \t6050000 read pairs finished. 877 secs passed\r\n"
]
},
{
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"Thread #5: \t6150000 read pairs finished. 879 secs passed\r\n"
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"Thread #1: \t6250000 read pairs finished. 880 secs passed\r\n"
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},
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"Thread #6: \t6200000 read pairs finished. 880 secs passed\r\n"
]
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{
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"Thread #3: \t6300000 read pairs finished. 881 secs passed\r\n"
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"Thread #7: \t6350000 read pairs finished. 881 secs passed\r\n"
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},
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"Thread #0: \t6400000 read pairs finished. 895 secs passed\r\n"
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},
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"text": [
"Thread #4: \t6450000 read pairs finished. 929 secs passed\r\n"
]
},
{
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"Thread #2: \t6500000 read pairs finished. 930 secs passed\r\n"
]
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"Thread #5: \t6550000 read pairs finished. 931 secs passed\r\n"
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"Thread #1: \t6600000 read pairs finished. 933 secs passed\r\n"
]
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{
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"Thread #6: \t6650000 read pairs finished. 934 secs passed\r\n"
]
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"Thread #3: \t6700000 read pairs finished. 934 secs passed\r\n"
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"Thread #7: \t6750000 read pairs finished. 935 secs passed\r\n"
]
},
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"stream": "stdout",
"text": [
"Thread #7: \t7109789 read pairs finished. 946 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #0: \t6800000 read pairs finished. 948 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t6850000 read pairs finished. 970 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #2: \t6900000 read pairs finished. 971 secs passed\r\n"
]
},
{
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"Thread #5: \t6950000 read pairs finished. 971 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7000000 read pairs finished. 971 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #6: \t7050000 read pairs finished. 972 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t7100000 read pairs finished. 972 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total number of aligned reads: \r\n",
"pairs: 4047153 (57%)\r\n",
"single a: 1332490 (19%)\r\n",
"single b: 1205101 (17%)\r\n",
"Done.\r\n",
"Finished at Fri Jan 30 13:03:30 2015\r\n",
"Total time consumed: 972 secs\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r\n",
"BSMAP v2.74\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Start at: Fri Jan 30 13:03:31 2015\r\n",
"\r\n",
"Input reference file: Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \t(format: FASTA)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Load in 7658 db seqs, total size 557717710 bp. 9 secs passed\r\n",
"total_kmers: 43046721\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Create seed table. 27 secs passed\r\n",
"max number of mismatches: read_length * 8% \tmax gap size: 0\r\n",
"kmer cut-off ratio: 5e-07\r\n",
"max multi-hits: 100\tmax Ns: 5\tseed size: 16\tindex interval: 4\r\n",
"quality cutoff: 0\tbase quality char: '!'\r\n",
"min fragment size:28\tmax fragemt size:500\r\n",
"start from read #1\tend at read #4294967295\r\n",
"additional alignment: T in reads => C in reference\r\n",
"mapping strand (read_1): ++,-+\r\n",
"mapping strand (read_2): +-,--\r\n",
"Pair-end alignment(8 threads)\r\n",
"Input read file #1: mcf_T3D5_R1.fastq \t(format: FASTQ)\r\n",
"Input read file #2: mcf_T3D5_R2.fastq \t(format: FASTQ)\r\n",
"Output file: bsmap_out_T3D5.sam\t (format: SAM)\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t50000 read pairs finished. 77 secs passed\r\n"
]
},
{
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"text": [
"Thread #0: \t100000 read pairs finished. 77 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t150000 read pairs finished. 78 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #4: \t200000 read pairs finished. 80 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #2: \t250000 read pairs finished. 80 secs passed\r\n"
]
},
{
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"text": [
"Thread #5: \t300000 read pairs finished. 81 secs passed\r\n"
]
},
{
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"Thread #6: \t350000 read pairs finished. 81 secs passed\r\n"
]
},
{
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"Thread #7: \t400000 read pairs finished. 82 secs passed\r\n"
]
},
{
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"Thread #3: \t450000 read pairs finished. 129 secs passed\r\n"
]
},
{
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]
},
{
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"Thread #4: \t600000 read pairs finished. 133 secs passed\r\n"
]
},
{
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"Thread #1: \t550000 read pairs finished. 133 secs passed\r\n"
]
},
{
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"Thread #2: \t650000 read pairs finished. 134 secs passed\r\n"
]
},
{
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"Thread #5: \t700000 read pairs finished. 134 secs passed\r\n"
]
},
{
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"Thread #6: \t750000 read pairs finished. 134 secs passed\r\n"
]
},
{
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]
},
{
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"Thread #0: \t900000 read pairs finished. 181 secs passed\r\n"
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{
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"Thread #3: \t850000 read pairs finished. 181 secs passed\r\n"
]
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"Thread #4: \t950000 read pairs finished. 185 secs passed\r\n"
]
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{
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"Thread #1: \t1000000 read pairs finished. 187 secs passed\r\n"
]
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{
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"Thread #2: \t1050000 read pairs finished. 187 secs passed\r\n"
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"Thread #5: \t1100000 read pairs finished. 188 secs passed\r\n"
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"Thread #6: \t1150000 read pairs finished. 188 secs passed\r\n"
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"Thread #7: \t1200000 read pairs finished. 188 secs passed\r\n"
]
},
{
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"Thread #0: \t1250000 read pairs finished. 233 secs passed\r\n"
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"Thread #0: \t1650000 read pairs finished. 286 secs passed\r\n"
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"Thread #4: \t1750000 read pairs finished. 290 secs passed\r\n"
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"Thread #7: \t2000000 read pairs finished. 297 secs passed\r\n"
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"Thread #1: \t3000000 read pairs finished. 451 secs passed\r\n"
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"text": [
"Thread #5: \t3100000 read pairs finished. 453 secs passed\r\n"
]
},
{
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"Thread #6: \t3150000 read pairs finished. 453 secs passed\r\n"
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{
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"Thread #7: \t3200000 read pairs finished. 456 secs passed\r\n"
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},
{
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"Thread #0: \t3250000 read pairs finished. 497 secs passed\r\n"
]
},
{
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{
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{
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"text": [
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"Thread #3: \t3750000 read pairs finished. 556 secs passed\r\n"
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{
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{
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"Thread #5: \t3900000 read pairs finished. 557 secs passed\r\n"
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"text": [
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"text": [
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},
{
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"Thread #0: \t4050000 read pairs finished. 603 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t4100000 read pairs finished. 606 secs passed\r\n"
]
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},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t4950000 read pairs finished. 715 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t5000000 read pairs finished. 716 secs passed\r\n"
]
},
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"text": [
"Thread #2: \t5050000 read pairs finished. 718 secs passed\r\n"
]
},
{
"output_type": "stream",
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"text": [
"Thread #5: \t5100000 read pairs finished. 718 secs passed\r\n"
]
},
{
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"text": [
"Thread #6: \t5150000 read pairs finished. 719 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t5200000 read pairs finished. 728 secs passed\r\n"
]
},
{
"output_type": "stream",
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"text": [
"Thread #0: \t5250000 read pairs finished. 761 secs passed\r\n"
]
},
{
"output_type": "stream",
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"text": [
"Thread #4: \t5300000 read pairs finished. 763 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t5350000 read pairs finished. 768 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t5400000 read pairs finished. 769 secs passed\r\n"
]
},
{
"output_type": "stream",
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"text": [
"Thread #2: \t5450000 read pairs finished. 770 secs passed\r\n"
]
},
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"output_type": "stream",
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"text": [
"Thread #5: \t5500000 read pairs finished. 771 secs passed\r\n"
]
},
{
"output_type": "stream",
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"text": [
"Thread #6: \t5550000 read pairs finished. 771 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t5600000 read pairs finished. 781 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t5650000 read pairs finished. 811 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t5700000 read pairs finished. 820 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t5850000 read pairs finished. 823 secs passed\r\n"
]
},
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"text": [
"Thread #5: \t5900000 read pairs finished. 823 secs passed\r\n"
]
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{
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"text": [
"Thread #6: \t5950000 read pairs finished. 824 secs passed\r\n"
]
},
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"text": [
"Thread #3: \t5800000 read pairs finished. 824 secs passed\r\n"
]
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"text": [
"Thread #1: \t5750000 read pairs finished. 825 secs passed\r\n"
]
},
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"text": [
"Thread #7: \t6000000 read pairs finished. 831 secs passed\r\n"
]
},
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"stream": "stdout",
"text": [
"Thread #0: \t6050000 read pairs finished. 863 secs passed\r\n"
]
},
{
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"text": [
"Thread #4: \t6100000 read pairs finished. 872 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #2: \t6150000 read pairs finished. 875 secs passed\r\n"
]
},
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"text": [
"Thread #5: \t6200000 read pairs finished. 876 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #6: \t6250000 read pairs finished. 877 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t6300000 read pairs finished. 878 secs passed\r\n"
]
},
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"text": [
"Thread #1: \t6350000 read pairs finished. 878 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t6400000 read pairs finished. 886 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t6450000 read pairs finished. 917 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t6500000 read pairs finished. 925 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t6550000 read pairs finished. 928 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t6600000 read pairs finished. 929 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t6650000 read pairs finished. 930 secs passed\r\n"
]
},
{
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"stream": "stdout",
"text": [
"Thread #3: \t6700000 read pairs finished. 931 secs passed\r\n"
]
},
{
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"text": [
"Thread #1: \t6750000 read pairs finished. 931 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #7: \t6800000 read pairs finished. 938 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #1: \t7125800 read pairs finished. 956 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #0: \t6850000 read pairs finished. 962 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #4: \t6900000 read pairs finished. 967 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #2: \t6950000 read pairs finished. 968 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #5: \t7000000 read pairs finished. 968 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #6: \t7050000 read pairs finished. 968 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Thread #3: \t7100000 read pairs finished. 968 secs passed\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Total number of aligned reads: \r\n",
"pairs: 4092568 (57%)\r\n",
"single a: 1250715 (18%)\r\n",
"single b: 1133306 (16%)\r\n",
"Done.\r\n",
"Finished at Fri Jan 30 13:19:39 2015\r\n",
"Total time consumed: 968 secs\r\n"
]
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"_methratio_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"methratio is a python script that accompanies BSMAP that determines methylation level on CpG loci"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"M1\",\"T1D3\",\"T1D5\", \"M3\", \"T3D3\", \"T3D5\"):\n",
" !python {bsmaploc}methratio.py \\\n",
"-d Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa \\\n",
"-u -z -g \\\n",
"-o methratio_out_{i}.txt \\\n",
"-s {bsmaploc}samtools \\\n",
"bsmap_out_{i}.sam \\\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:19:42 2015: reading reference Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:20:16 2015: reading bsmap_out_M1.sam ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[samopen] SAM header is present: 7658 sequences.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\t@ Fri Jan 30 13:24:53 2015: read 10000000 lines\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:25:17 2015: combining CpG methylation from both strands ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:25:41 2015: writing methratio_out_M1.txt ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:34:47 2015: done.\r\n",
"total 8716465 valid mappings, 48671764 covered cytosines, average coverage: 1.78 fold.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:34:49 2015: reading reference Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:35:22 2015: reading bsmap_out_T1D3.sam ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[samopen] SAM header is present: 7658 sequences.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:37:50 2015: combining CpG methylation from both strands ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:38:14 2015: writing methratio_out_T1D3.txt ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:43:41 2015: done.\r\n",
"total 5759214 valid mappings, 26507296 covered cytosines, average coverage: 1.32 fold.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:43:43 2015: reading reference Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:44:17 2015: reading bsmap_out_T1D5.sam ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[samopen] SAM header is present: 7658 sequences.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:48:13 2015: combining CpG methylation from both strands ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:48:37 2015: writing methratio_out_T1D5.txt ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:57:04 2015: done.\r\n",
"total 6974209 valid mappings, 45446473 covered cytosines, average coverage: 1.54 fold.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:57:07 2015: reading reference Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 13:57:40 2015: reading bsmap_out_M3.sam ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[samopen] SAM header is present: 7658 sequences.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\t@ Fri Jan 30 14:02:22 2015: read 10000000 lines\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:03:08 2015: combining CpG methylation from both strands ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:03:32 2015: writing methratio_out_M3.txt ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:13:17 2015: done.\r\n",
"total 9773223 valid mappings, 53389886 covered cytosines, average coverage: 1.78 fold.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:13:19 2015: reading reference Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:13:53 2015: reading bsmap_out_T3D3.sam ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[samopen] SAM header is present: 7658 sequences.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\t@ Fri Jan 30 14:18:33 2015: read 10000000 lines\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:18:50 2015: combining CpG methylation from both strands ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:19:14 2015: writing methratio_out_T3D3.txt ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:28:54 2015: done.\r\n",
"total 8847902 valid mappings, 52255860 covered cytosines, average coverage: 1.65 fold.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:28:56 2015: reading reference Crassostrea_gigas.GCA_000297895.1.22.dna_sm.genome.fa ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:29:29 2015: reading bsmap_out_T3D5.sam ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[samopen] SAM header is present: 7658 sequences.\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\t@ Fri Jan 30 14:34:12 2015: read 10000000 lines\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:34:27 2015: combining CpG methylation from both strands ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:34:51 2015: writing methratio_out_T3D5.txt ...\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@ Fri Jan 30 14:44:26 2015: done.\r\n",
"total 8808414 valid mappings, 51732152 covered cytosines, average coverage: 1.69 fold.\r\n"
]
}
],
"prompt_number": 8
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Global Differences: methylkit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Converting methratio files for methylkit**"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#first methratio files are converted to filter for CG context, 3x coverage (mr3x.awk), and reformatting (mr_gg.awk.sh).\n",
"#due to issue passing variable to awk, simple scripts were used (included in repository)\n",
"for i in (\"M1\",\"T1D3\",\"T1D5\", \"M3\", \"T3D3\", \"T3D5\"):\n",
" !echo {i}\n",
" !grep \"[A-Z][A-Z]CG[A-Z]\" <methratio_out_{i}.txt> methratio_out_{i}CG.txt\n",
" !awk -f ../scripts/mr3x.awk methratio_out_{i}CG.txt > mr3x.{i}.txt\n",
" !awk -f ../scripts/mr_gg.awk.sh mr3x.{i}.txt > mkfmt_{i}.txt\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"M1\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"T1D3\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"T1D5\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"M3\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"T3D3\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"T3D5\r\n"
]
}
],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Running R > methylkit**"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%load_ext rpy2.ipython\n"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 11
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"#UNCOMMENT IF YOU NEED TO INSTALL PACKAGES\n",
"# dependencies\n",
"#install.packages( c(\"data.table\",\"devtools\"))\n",
"#source(\"http://bioconductor.org/biocLite.R\")\n",
"#biocLite(c(\"GenomicRanges\",\"IRanges\"))\n",
"\n",
"# install the development version from github\n",
"#library(devtools)\n",
"#install_github(\"al2na/methylKit\",build_vignettes=FALSE)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"NULL\n"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%R library(methylKit)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 13,
"text": [
"array(['methylKit', 'tools', 'stats', 'graphics', 'grDevices', 'utils',\n",
" 'datasets', 'methods', 'base'], \n",
" dtype='|S9')"
]
}
],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R file.list <- list \n",
"('mkfmt_M1.txt',\n",
" 'mkfmt_T1D3.txt',\n",
" 'mkfmt_T1D5.txt',\n",
" 'mkfmt_M3.txt',\n",
" 'mkfmt_T3D3.txt',\n",
" 'mkfmt_T3D5.txt'\n",
")\n"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"myobj=read(file.list,sample.id=list(\"1_sperm\",\"1_72hpf\",\"1_120hpf\",\"3_sperm\",\"3_72hpf\",\"3_120hpf\"),assembly=\"v9\",treatment=c(0,0,0,1,1,1))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"meth<-unite(myobj)\n",
"#getCorrelation(meth,plot=T)\n",
"hc<- clusterSamples(meth, dist=\"correlation\", method=\"ward\", plot=T)\n",
"#PCA<-PCASamples(meth)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"The \"ward\" method has been renamed to \"ward.D\"; note new \"ward.D2\"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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oGWOMMIUESIAESIAE/ETAegMM1/G4ceP8xJy6kAAJkAAJkIBY44J26wLjfnfv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\nkcD/Ay67A1+IV3H0AAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 16
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Differentially methylated loci"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Determining differentially methylated loci using methylkit\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"#Family-specific DMLs\n",
"#note that file.list was defined in prior section\n",
"DMLobj=read(file.list,sample.id=list(\"M1\",\"T1D3\",\"T1D5\",\"M3\",\"T3D3\",\"T3D5\"),assembly=\"v9\",treatment=c(1,1,1,0,0,0), context=\"CpG\")\n",
"lin<-unite(DMLobj)\n",
"lin.pooled <- pool(lin, sample.ids <- c(\"lin_1\", \"lin_3\"))\n",
"lin_DML.fisher <- calculateDiffMeth(lin.pooled)\n",
"select(lin_DML.fisher, 1)\n",
"lin_DML_p <- getData(lin_DML.fisher)\n",
"lin_DML_filt <- lin_DML_p[lin_DML_p$pvalue < 0.01 & lin_DML_p$meth.diff > 25,]\n",
"write.csv(lin_DML_filt,file=\"lin_DML_filt\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l lin_DML_filt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 190 lin_DML_filt\r\n"
]
}
],
"prompt_number": 18
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"####Differentially methylated loci during development. \n",
"This is done by doing three pairwise comparisons"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R file.list <- list \n",
"('mkfmt_M1.txt',\n",
" 'mkfmt_T1D3.txt',\n",
" 'mkfmt_M3.txt',\n",
" 'mkfmt_T3D3.txt'\n",
")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R \n",
"#Developmentally different DMLs (Males v Day3)\n",
"DMLobj=read(file.list,sample.id=list(\"M1\",\"T1D3\",\"M3\",\"T3D3\"), assembly=\"v9\",treatment=c(1,0,1,0), context=\"CpG\")\n",
"DevelMvD3<-unite(DMLobj)\n",
"DevelMvD3.pooled <- pool(DevelMvD3, sample.ids <- c(\"Males\", \"Day3\"))\n",
"DevelMvD3_DML.fisher <- calculateDiffMeth(DevelMvD3.pooled)\n",
"select(DevelMvD3_DML.fisher, 1)\n",
"DevelMvD3_DML_p <- getData(DevelMvD3_DML.fisher)\n",
"DevelMvD3_DML_filt <- DevelMvD3_DML_p[DevelMvD3_DML_p$pvalue < 0.01 & DevelMvD3_DML_p$meth.diff > 25,]\n",
"write.csv(DevelMvD3_DML_filt,file=\"DevelMvD3_DML_filt\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l DevelMvD3_DML_filt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 30 DevelMvD3_DML_filt\r\n"
]
}
],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R file.list <- list \n",
"('mkfmt_M1.txt',\n",
" 'mkfmt_T1D5.txt',\n",
" 'mkfmt_M3.txt',\n",
" 'mkfmt_T3D5.txt'\n",
")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R \n",
"#Developmentally different DMLs (Males v Day5)\n",
"DMLobj=read(file.list,sample.id=list(\"M1\",\"T1D5\",\"M3\",\"T3D5\"), assembly=\"v9\",treatment=c(1,0,1,0), context=\"CpG\")\n",
"DevelMvD5<-unite(DMLobj)\n",
"DevelMvD5.pooled <- pool(DevelMvD5, sample.ids <- c(\"Males\", \"Day5\"))\n",
"DevelMvD5_DML.fisher <- calculateDiffMeth(DevelMvD5.pooled)\n",
"select(DevelMvD5_DML.fisher, 1)\n",
"DevelMvD5_DML_p <- getData(DevelMvD5_DML.fisher)\n",
"DevelMvD5_DML_filt <- DevelMvD5_DML_p[DevelMvD5_DML_p$pvalue < 0.01 & DevelMvD5_DML_p$meth.diff > 25,]\n",
"write.csv(DevelMvD5_DML_filt,file=\"DevelMvD5_DML_filt\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 23
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l DevelMvD5_DML_filt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 86 DevelMvD5_DML_filt\r\n"
]
}
],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R file.list <- list \n",
"('mkfmt_T1D3.txt',\n",
" 'mkfmt_T1D5.txt',\n",
" 'mkfmt_T3D3.txt',\n",
" 'mkfmt_T3D5.txt'\n",
")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 25
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R \n",
"#Developmentally different DMLs (Day3 v Day5)\n",
"DMLobj=read(file.list,sample.id=list(\"T1D3\",\"T1D5\",\"T3D3\",\"T3D5\"), assembly=\"v9\",treatment=c(1,0,1,0), context=\"CpG\")\n",
"DevelD3vD5<-unite(DMLobj)\n",
"DevelD3vD5.pooled <- pool(DevelD3vD5, sample.ids <- c(\"Day3\", \"Day5\"))\n",
"DevelD3vD5_DML.fisher <- calculateDiffMeth(DevelD3vD5.pooled)\n",
"select(DevelD3vD5_DML.fisher, 1)\n",
"DevelD3vD5_DML_p <- getData(DevelD3vD5_DML.fisher)\n",
"DevelD3vD5_DML_filt <- DevelD3vD5_DML_p[DevelD3vD5_DML_p$pvalue < 0.01 & DevelD3vD5_DML_p$meth.diff > 25,]\n",
"write.csv(DevelD3vD5_DML_filt,file=\"DevelD3vD5_DML_filt\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l DevelD3vD5_DML_filt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 47 DevelD3vD5_DML_filt\r\n"
]
}
],
"prompt_number": 27
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#removing column titles\n",
"!tail -n +2 DevelMvD5_DML_filt > DevelMvD5_DML\n",
"!tail -n +2 DevelD3vD5_DML_filt > DevelD3vD5_DML "
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 28
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Concatenate all developmetnally different DMLs to one file\n",
"!cat DevelMvD3_DML_filt DevelMvD5_DML DevelD3vD5_DML > Devel_DML_filt"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 29
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l Devel_DML_filt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 161 Devel_DML_filt\r\n"
]
}
],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"###Creating DML BED files"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!tail -n +2 lin_DML_filt | awk -F, '{print $2, $3, $4, \"DML_lin\" }' | tr -d '\"' | tr ' ' \"\\t\" > lineage_dml.bed"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 31
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l lineage_dml.bed"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 189 lineage_dml.bed\r\n"
]
}
],
"prompt_number": 32
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!tail -n +2 Devel_DML_filt | awk -F, '{print $2, $3, $4, \"DML_dev\" }' | tr -d '\"' | tr ' ' \"\\t\" > dev_dml.bed"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 33
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l dev_dml.bed"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 160 dev_dml.bed\r\n"
]
}
],
"prompt_number": 34
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Genomic location of DMLs"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#In order to find location of DMLs oyster genome tracks will be downloaded\n",
"#and intersectbed (bedtools suite) run\n",
"#Note track with all CG's is large (~977mb)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 35
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cd genome_tracks\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"/Users/Steven/Desktop/olson-ms-nb-master/wd/genome_tracks\n"
]
}
],
"prompt_number": 69
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"exon\",\"intron\",\"TE\",\"gene\",\"1k5p_gene_promoter\",\"CG\"):\n",
" !curl -O http://eagle.fish.washington.edu/trilobite/Crassostrea_gigas_v9_tracks/Cgigas_v9_{i}.gff \n",
"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 11.7M 100 11.7M 0 0 20.3M 0 --:--:-- --:--:-- --:--:-- 48.7M\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 12.0M 100 12.0M 0 0 52.7M 0 --:--:-- --:--:-- --:--:-- 53.1M\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 6325k 100 6325k 0 0 44.8M 0 --:--:-- --:--:-- --:--:-- 45.4M\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 1777k 100 1777k 0 0 32.2M 0 --:--:-- --:--:-- --:--:-- 33.3M\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 1848k 100 1848k 0 0 32.8M 0 --:--:-- --:--:-- --:--:-- 34.0M\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 4 932M 4 39.3M 0 0 71.7M 0 0:00:12 --:--:-- 0:00:12 71.9M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 13 932M 13 130M 0 0 84.0M 0 0:00:11 0:00:01 0:00:10 84.1M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 23 932M 23 217M 0 0 85.1M 0 0:00:10 0:00:02 0:00:08 85.1M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 28 932M 28 269M 0 0 75.8M 0 0:00:12 0:00:03 0:00:09 75.8M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 38 932M 38 358M 0 0 78.7M 0 0:00:11 0:00:04 0:00:07 78.8M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 47 932M 47 443M 0 0 79.8M 0 0:00:11 0:00:05 0:00:06 80.7M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 57 932M 57 535M 0 0 81.8M 0 0:00:11 0:00:06 0:00:05 81.0M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 62 932M 62 586M 0 0 77.6M 0 0:00:11 0:00:07 0:00:04 73.8M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 73 932M 73 682M 0 0 79.8M 0 0:00:11 0:00:08 0:00:03 82.6M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 81 932M 81 763M 0 0 79.9M 0 0:00:11 0:00:09 0:00:02 80.9M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 90 932M 90 844M 0 0 79.7M 0 0:00:11 0:00:10 0:00:01 79.5M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
" 97 932M 97 909M 0 0 78.3M 0 0:00:11 0:00:11 --:--:-- 73.9M"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 932M 100 932M 0 0 78.7M 0 0:00:11 0:00:11 --:--:-- 80.7M\r\n"
]
}
],
"prompt_number": 37
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"TE-TANDEMREPEAT\", \"TE-WUBLASTX\"):\n",
" !curl -O http://eagle.fish.washington.edu/trilobite/Crassostrea_gigas_v9_tracks/Cgigas_v9_{i}.gff \n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 3196k 100 3196k 0 0 38.5M 0 --:--:-- --:--:-- --:--:-- 40.0M\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" % Total % Received % Xferd Average Speed Time Time Time Current\r\n",
" Dload Upload Total Spent Left Speed\r\n",
"\r",
" 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\r",
"100 3129k 100 3129k 0 0 57.3M 0 --:--:-- --:--:-- --:--:-- 59.9M\r\n"
]
}
],
"prompt_number": 70
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cd .."
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"/Users/Steven/Desktop/olson-ms-nb-master/wd\n"
]
}
],
"prompt_number": 71
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"exon\",\"intron\",\"TE\",\"1k5p_gene_promoter\",\"TE-TANDEMREPEAT\", \"TE-WUBLASTX\"):\n",
" !intersectbed \\\n",
" -u \\\n",
" -a lineage_dml.bed \\\n",
" -b ./genome_tracks/Cgigas_v9_{i}.gff \\\n",
" > {i}_intersect_DML_lin_u.txt\n",
" !wc -l {i}_intersect_DML_lin_u.txt > lin{i}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 72
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!head linTE\n",
"!head linTE-WUBLASTX\n",
"!head linTE-TANDEMREPEAT\n",
"!head linintron\n",
"!head linexon\n",
"!head lin1k5p_gene_promoter"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 27 TE_intersect_DML_lin_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 24 TE-WUBLASTX_intersect_DML_lin_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 3 TE-TANDEMREPEAT_intersect_DML_lin_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 42 intron_intersect_DML_lin_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 25 exon_intersect_DML_lin_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 8 1k5p_gene_promoter_intersect_DML_lin_u.txt\r\n"
]
}
],
"prompt_number": 77
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Concatenate counts of genomic regions into one table for lineage-specific DMLs\n",
"!cat linintron linexon lin1k5p_gene_promoter linTE-TANDEMREPEAT linTE-WUBLASTX> lintable"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 78
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk 'FNR==NR{sum+=$1;next}; {print $0,sum}' lintable{,} > lin_total"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 79
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $2, $1, $3, (($1/$3)*100)}' lin_total > lineage_DMLs"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 80
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"exon\",\"intron\",\"TE-TANDEMREPEAT\", \"TE-WUBLASTX\", \"TE\", \"1k5p_gene_promoter\"):\n",
" !intersectbed \\\n",
" -u \\\n",
" -a dev_dml.bed \\\n",
" -b ./genome_tracks/Cgigas_v9_{i}.gff \\\n",
" > {i}_intersect_DML_dev_u.txt\n",
" !wc -l {i}_intersect_DML_dev_u.txt > dev{i}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 81
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!head devTE\n",
"!head devTE-WUBLASTX\n",
"!head devTE-TANDEMREPEAT\n",
"!head devintron\n",
"!head devexon\n",
"!head dev1k5p_gene_promoter"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 20 TE_intersect_DML_dev_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 11 TE-WUBLASTX_intersect_DML_dev_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 9 TE-TANDEMREPEAT_intersect_DML_dev_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 60 intron_intersect_DML_dev_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 13 exon_intersect_DML_dev_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 6 1k5p_gene_promoter_intersect_DML_dev_u.txt\r\n"
]
}
],
"prompt_number": 83
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Concatenate counts of genomic regions into one table for developmentally different DMLs\n",
"!cat devintron devexon dev1k5p_gene_promoter devTE-TANDEMREPEAT devTE-WUBLASTX > devtable"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 84
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!head devtable"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 60 intron_intersect_DML_dev_u.txt\r\n",
" 13 exon_intersect_DML_dev_u.txt\r\n",
" 6 1k5p_gene_promoter_intersect_DML_dev_u.txt\r\n",
" 9 TE-TANDEMREPEAT_intersect_DML_dev_u.txt\r\n",
" 11 TE-WUBLASTX_intersect_DML_dev_u.txt\r\n"
]
}
],
"prompt_number": 86
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk 'FNR==NR{sum+=$1;next}; {print $0,sum}' devtable{,} > dev_total\n",
"!head dev_total"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 60 intron_intersect_DML_dev_u.txt 99\r\n",
" 13 exon_intersect_DML_dev_u.txt 99\r\n",
" 6 1k5p_gene_promoter_intersect_DML_dev_u.txt 99\r\n",
" 9 TE-TANDEMREPEAT_intersect_DML_dev_u.txt 99\r\n",
" 11 TE-WUBLASTX_intersect_DML_dev_u.txt 99\r\n"
]
}
],
"prompt_number": 87
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $2, $1, $3, (($1/$3)*100)}' dev_total > developmental_DMLs\n",
"!head developmental_DMLs"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"intron_intersect_DML_dev_u.txt 60 99 60.6061\r\n",
"exon_intersect_DML_dev_u.txt 13 99 13.1313\r\n",
"1k5p_gene_promoter_intersect_DML_dev_u.txt 6 99 6.06061\r\n",
"TE-TANDEMREPEAT_intersect_DML_dev_u.txt 9 99 9.09091\r\n",
"TE-WUBLASTX_intersect_DML_dev_u.txt 11 99 11.1111\r\n"
]
}
],
"prompt_number": 88
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for i in (\"exon\",\"intron\",\"TE-TANDEMREPEAT\", \"TE-WUBLASTX\",\"gene\",\"1k5p_gene_promoter\"):\n",
" !intersectbed \\\n",
" -u \\\n",
" -a ./genome_tracks/Cgigas_v9_CG.gff \\\n",
" -b ./genome_tracks/Cgigas_v9_{i}.gff \\\n",
" > {i}_intersect_CG_u.txt\n",
" !wc -l {i}_intersect_CG_u.txt > CG{i}"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 93
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!head CGintron\n",
"!head CGexon \n",
"!head CG1k5p_gene_promoter \n",
"!head CGTE\n",
"!head CGTE-TANDEMREPEAT\n",
"!head CGTE-WUBLASTX"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 2815997 intron_intersect_CG_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 1129658 exon_intersect_CG_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 593081 1k5p_gene_promoter_intersect_CG_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 589509 TE_intersect_CG_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 173095 TE-TANDEMREPEAT_intersect_CG_u.txt\r\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 416439 TE-WUBLASTX_intersect_CG_u.txt\r\n"
]
}
],
"prompt_number": 94
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Concatenate counts of genomic regions into one table for all CGs in oyster genome\n",
"!cat CGintron CGexon CG1k5p_gene_promoter CGTE-TANDEMREPEAT CGTE-WUBLASTX > CGtable"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 95
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk 'FNR==NR{sum+=$1;next}; {print $0,sum}' CGtable{,} > CG_total"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 96
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $2, $1, $3, (($1/$3)*100)}' CG_total > all_CGs"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 97
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!paste -d\" \" lineage_DMLs developmental_DMLs all_CGs > StackedBars"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 98
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $4, $8, $12}' StackedBars | tr ' ' \"\\t\" > StackedBars_DMLs"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 99
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!head StackedBars"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"intron_intersect_DML_lin_u.txt 42 102 41.1765 intron_intersect_DML_dev_u.txt 60 99 60.6061 intron_intersect_CG_u.txt 2815997 5128270 54.9112\r\n",
"exon_intersect_DML_lin_u.txt 25 102 24.5098 exon_intersect_DML_dev_u.txt 13 99 13.1313 exon_intersect_CG_u.txt 1129658 5128270 22.0281\r\n",
"1k5p_gene_promoter_intersect_DML_lin_u.txt 8 102 7.84314 1k5p_gene_promoter_intersect_DML_dev_u.txt 6 99 6.06061 1k5p_gene_promoter_intersect_CG_u.txt 593081 5128270 11.5649\r\n",
"TE-TANDEMREPEAT_intersect_DML_lin_u.txt 3 102 2.94118 TE-TANDEMREPEAT_intersect_DML_dev_u.txt 9 99 9.09091 TE-TANDEMREPEAT_intersect_CG_u.txt 173095 5128270 3.37531\r\n",
"TE-WUBLASTX_intersect_DML_lin_u.txt 24 102 23.5294 TE-WUBLASTX_intersect_DML_dev_u.txt 11 99 11.1111 TE-WUBLASTX_intersect_CG_u.txt 416439 5128270 8.12046\r\n"
]
}
],
"prompt_number": 100
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!head StackedBars_DMLs"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"41.1765\t60.6061\t54.9112\r\n",
"24.5098\t13.1313\t22.0281\r\n",
"7.84314\t6.06061\t11.5649\r\n",
"2.94118\t9.09091\t3.37531\r\n",
"23.5294\t11.1111\t8.12046\r\n"
]
}
],
"prompt_number": 101
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Stacked Bar Plot of DMLs versus all CGs"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R \n",
"DMLs<-as.matrix(read.table('StackedBars_DMLs', header=F))\n",
"colnames(DMLs)<-c(\"Lin DMLs\",\"Devel DMLs\", \"All CpGs\")\n",
"par(mar=c(5.1, 4.1, 4.1, 8.1), xpd=T)\n",
"par(xpd=T, mar=par()$mar+c(0,0,0,5))\n",
"barplot(as.matrix(DMLs), col=c(\"#99983B\", \"#2F583B\", \"#4A7958\",\"#8DAB96\",\"#B34321\"), ylab=\"Proportion of CpG within a genomic region (%)\")\n",
"legend(\"topright\",inset=c(-0.63,-0), legend=c(\"Intron\", \"Exon\", \"Promoter Region\", \"Tandem\", \"TE-WUblast\"), pch=c(19,19,19), col=c(\"#99983B\", \"#2F583B\", \"#4A7958\",\"#8DAB96\",\"#B34321\"))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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CCMSvAAE4fj87zhwBBBBAII4FCMBx/OFx6gggUPgCv2/bYl/MnWlzFn5rGRkZucqwZ8+e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\n"
}
],
"prompt_number": 138
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Statistical Analysis (Chi-squared test)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Formatting family-specific DML files for stats\n",
"!wc -l lineage_dml.bed > lineage_countstotal\n",
"!head lineage_countstotal"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 189 lineage_dml.bed\r\n"
]
}
],
"prompt_number": 122
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!wc -l ./genome_tracks/Cgigas_v9_CG.gff > CG_countstotal\n",
"!head CG_countstotal"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 10035701 ./genome_tracks/Cgigas_v9_CG.gff\r\n"
]
}
],
"prompt_number": 123
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!cat linTE lineage_countstotal > Lineage_TEs\n",
"!head Lineage_TEs"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 27 TE_intersect_DML_lin_u.txt\r\n",
" 189 lineage_dml.bed\r\n"
]
}
],
"prompt_number": 115
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1}' Lineage_TEs > Lineage_TEs_counts\n",
"!head Lineage_TEs_counts"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"27\r\n",
"189\r\n"
]
}
],
"prompt_number": 116
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!cat CGTE CG_countstotal > CG_TEs\n",
"!head CG_TEs"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 589509 TE_intersect_CG_u.txt\r\n",
" 10035701 ./genome_tracks/Cgigas_v9_CG.gff\r\n"
]
}
],
"prompt_number": 117
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1}' CG_TEs > CG_TEs_counts\n",
"!head CG_TEs_counts"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"589509\r\n",
"10035701\r\n"
]
}
],
"prompt_number": 118
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!paste Lineage_TEs_counts CG_TEs_counts > LinTEs_combined\n",
"!head LinTEs_combined"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"27\t589509\r\n",
"189\t10035701\r\n"
]
}
],
"prompt_number": 119
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1, $2}' LinTEs_combined > Lineage_TEs_stats\n",
"!head Lineage_TEs_stats"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"27 589509\r\n",
"189 10035701\r\n"
]
}
],
"prompt_number": 120
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"#Stats for TEs: family-specific\n",
"LinStats<- read.table('Lineage_TEs_stats')\n",
"chisq.test(LinStats)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"\tPearson's Chi-squared test with Yates' continuity correction\n",
"\n",
"data: LinStats\n",
"X-squared = 18.6144, df = 1, p-value = 1.6e-05\n",
"\n"
]
}
],
"prompt_number": 121
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"NEW TE-WUBLAST- Lineage"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!cat linTE-WUBLASTX lineage_countstotal > Lineage_TE-WUs\n",
"!head Lineage_TE-WUs"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 24 TE-WUBLASTX_intersect_DML_lin_u.txt\r\n",
" 189 lineage_dml.bed\r\n"
]
}
],
"prompt_number": 132
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1}' Lineage_TE-WUs > Lineage_TE-WUs_counts\n",
"!head Lineage_TE-WUs_counts"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"24\r\n",
"189\r\n"
]
}
],
"prompt_number": 133
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!cat CGTE-WUBLASTX CG_countstotal > CG_TE_WUs\n",
"!head CG_TE_WUs"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 416439 TE-WUBLASTX_intersect_CG_u.txt\r\n",
" 10035701 ./genome_tracks/Cgigas_v9_CG.gff\r\n"
]
}
],
"prompt_number": 127
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1}' CG_TE_WUs > CG_TE_WUs_counts\n",
"!head CG_TE_WUs_counts"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"416439\r\n",
"10035701\r\n"
]
}
],
"prompt_number": 128
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!paste Lineage_TE-WUs_counts CG_TE_WUs_counts > LinTE_WUs_combined\n",
"!head LinTE_WUs_combined"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"24\t416439\r\n",
"189\t10035701\r\n"
]
}
],
"prompt_number": 134
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1, $2}' LinTE_WUs_combined > Lineage_TE_WUs_stats\n",
"!head Lineage_TE_WUs_stats"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"24 416439\r\n",
"189 10035701\r\n"
]
}
],
"prompt_number": 135
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"#Stats for TEs: family-specific\n",
"LinStats<- read.table('Lineage_TE_WUs_stats')\n",
"chisq.test(LinStats)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"\tPearson's Chi-squared test with Yates' continuity correction\n",
"\n",
"data: LinStats\n",
"X-squared = 27.6614, df = 1, p-value = 1.445e-07\n",
"\n"
]
}
],
"prompt_number": 136
},
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"\n",
"NEW TE-WUBLAST- Development"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img src=\"http://eagle.fish.washington.edu/cnidarian/skitch/genefish_1A7D6AE3.png\" alt=\"genefish_1A7D6AE3.png\"/>"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#formatting developmental DML files for stats\n",
"!wc -l dev_dml.bed > dev_countstotal"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 140
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!cat devTE-WUBLASTX dev_countstotal > Dev_TE_WUs"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 146
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1}' Dev_TE_WUs > Dev_TE_WUs_counts"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 147
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!paste Dev_TE_WUs_counts CG_TE_WUs_counts > DevTE_WUs_combined"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 148
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1, $2}' DevTE_WUs_combined > Dev_TE_WUs_stats"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 150
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"#Stats for TEs: developmentally different\n",
"DevStats<-read.table('Dev_TE_WUs_stats')\n",
"chisq.test(DevStats)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"text": [
"\n",
"\tPearson's Chi-squared test with Yates' continuity correction\n",
"\n",
"data: DevStats\n",
"X-squared = 2.0779, df = 1, p-value = 0.1494\n",
"\n"
]
}
],
"prompt_number": 151
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 145
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#formatting developmental DML files for stats\n",
"!wc -l dev_dml.bed > dev_countstotal\n",
"!head dev_countstotal"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 160 dev_dml.bed\r\n"
]
}
],
"prompt_number": 112
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!cat devTE-TANDEMREPEAT dev_countstotal > Dev_TE-TANDEM\n",
"!head Dev_TE-TANDEM"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" 9 TE-TANDEMREPEAT_intersect_DML_dev_u.txt\r\n",
" 160 dev_dml.bed\r\n"
]
}
],
"prompt_number": 124
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1}' Dev_TE-TANDEM > Dev_TE-TANDEM_counts\n",
"!head Dev_TE-TANDEM_counts"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"9\r\n",
"160\r\n"
]
}
],
"prompt_number": 125
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!paste Dev_TE-TANDEM_counts CG_TE-_counts > DevTEs_combined"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"paste: Dev_TE-TANDEM_counts: No such file or directory\r\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"!awk '{print $1, $2}' DevTEs_combined > Dev_TEs_stats"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%R\n",
"#Stats for TEs: developmentally different\n",
"DevStats<-read.table('Dev_TEs_stats')\n",
"chisq.test(DevStats)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"ERROR: Cell magic `%%R` not found.\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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