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tutorial_RAD_3.0.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:52329c6ebe88188c347c3ab84c95453fa7f24650c99964fb2df85ab00334d24a"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Example _de novo_ RADseq assembly using _pyRAD_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---------- \n",
"\n",
"Please direct questions about _pyRAD_ analyses to the google group thread ([link](https://groups.google.com/forum/#!forum/pyrad-users)) \n",
"\n",
"-------------- \n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"+ This tutorial is meant as a walkthrough for a single-end RADseq analyses. If you have not yet read the [__full tutorial__](http://www.dereneaton.com/software/pyrad), you should start there for a broader description of how _pyRAD_ works. If you are new to RADseq analyses, this tutorial will provide a simple overview of how to execute _pyRAD_, what the data files look like, and how to check that your analysis is working, and the expected output formats. \n",
"\n",
"\n",
"\n",
"+ Each cell in this tutorial begins with the header (%%bash) indicating that the code should be executed in a command line shell, for example by copying and pasting the text into your terminal (but excluding the %%bash header).\n",
"\n",
"------------- \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Begin by executing the command below. This will download an example simulated RADseq data set and unarchive it into your current directory."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"wget -q dereneaton.com/downloads/simRADs.zip\n",
"unzip simRADs.zip"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Archive: simRADs.zip\n",
" inflating: simRADs.barcodes \n",
" inflating: simRADs_R1.fastq.gz \n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---------------- \n",
"\n",
"#### The two necessary files below should now be located in your current directory.\n",
"\n",
"+ simRADs.fastq.gz : Illumina fastQ formatted reads (gzip compressed)\n",
"+ simRADs.barcodes : barcode map file \n",
"\n",
"----------------- \n",
"\n"
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"We begin by creating the params.txt file which is used to set all parameters for an analysis."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"## I have pyRAD in my $PATH so that I can call it by simply typing pyRAD.\n",
"## If you haven't done this then you will need to type the full path to \n",
"## the pyRAD script to execute it.\n",
"\n",
"## call pyRAD with the (-n) option\n",
"pyRAD -n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\tnew params.txt file created\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"------------ \n",
"\n",
"The params file lists on each line one parameter followed by a __##__ mark, after which any comments can be left. In the comments section there is a description of the parameter and in parentheses the step of the analysis affected by the parameter. Lines 1-12 are required, the remaining lines are optional. The params.txt file is further described in the general tutorial."
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Let's take a look at the default settings. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"cat params.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"==** parameter inputs for pyRAD version 3.0a **========================== affected step ==\n",
"./ ## 1. Working directory (all)\n",
"./*.fastq.gz ## 2. Loc. of non-demultiplexed files (if not line 16) (s1)\n",
"./*.barcodes ## 3. Loc. of barcode file (if not line 16) (s1)\n",
"vsearch ## 4. command (or path) to call vsearch (or usearch) (s3,s6)\n",
"muscle ## 5. command (or path) to call muscle (s3,s7)\n",
"TGCAG ## 6. Restriction overhang (e.g., C|TGCAG -> TGCAG) (s1,s2)\n",
"2 ## 7. N processors (parallel) (all)\n",
"6 ## 8. Mindepth: min coverage for a cluster (s4,s5)\n",
"4 ## 9. NQual: max # sites with qual < 20 (line 18) (s2)\n",
".88 ## 10. Wclust: clustering threshold as a decimal (s3,s6)\n",
"rad ## 11. Datatype: rad,gbs,ddrad,pairgbs,pairddrad,merge (all)\n",
"4 ## 12. MinCov: min samples in a final locus (s7)\n",
"3 ## 13. MaxSH: max inds with shared hetero site (s7)\n",
"c88d6m4p3 ## 14. Prefix name for final output (no spaces) (s7)\n",
"==== optional params below this line =================================== affected step ==\n",
" ## 15.opt.: select subset (prefix* only selector) (s2-s7)\n",
" ## 16.opt.: add-on (outgroup) taxa (list or prefix*) (s6,s7)\n",
" ## 17.opt.: exclude taxa (list or prefix*) (s7)\n",
" ## 18.opt.: loc. of de-multiplexed data (s2)\n",
" ## 19.opt.: maxM: N mismatches in barcodes (def= 1) (s1)\n",
" ## 20.opt.: phred Qscore offset (def= 33) (s2)\n",
" ## 21.opt.: filter: def=0=NQual 1=NQual+adapters. 2=strict (s2)\n",
" ## 22.opt.: a priori E,H (def= 0.001,0.01, if not estimated) (s5)\n",
" ## 23.opt.: maxN: max Ns in a cons seq (def=5) (s5)\n",
" ## 24.opt.: maxH: max heterozyg. sites in cons seq (def=5) (s5)\n",
" ## 25.opt.: ploidy: max alleles in cons seq (def=2;see docs) (s4,s5)\n",
" ## 26.opt.: maxSNPs: (def=100). Paired (def=100,100) (s7)\n",
" ## 27.opt.: maxIndels: within-clust,across-clust (def. 3,99) (s3,s7)\n",
" ## 28.opt.: random number seed (def. 112233) (s3,s6,s7)\n",
" ## 29.opt.: trim overhang left,right on final loci, def(0,0) (s7)\n",
" ## 30.opt.: output formats: p,n,a,s,v,u,t,m,k,g,* (see docs) (s7)\n",
" ## 31.opt.: call maj. consens if depth < stat. limit (def=0) (s5)\n",
" ## 32.opt.: keep trimmed reads (def=0). Enter min length. (s2)\n",
" ## 33.opt.: max stack size (int), def= max(500,mean+2*SD) (s3)\n",
" ## 34.opt.: minDerep: exclude dereps with <= N copies, def=1 (s3)\n",
" ## 35.opt.: use hierarchical clustering (def.=0, 1=yes) (s6)\n",
" ## 36.opt.: repeat masking (def.=1='dust' method, 0=no) (s3,s6)\n",
" ## 37.opt.: vsearch threads per job (def.=6; see docs) (s3,s6)\n",
"==== optional: list group/clade assignments below this line (see docs) ==================\n"
]
}
],
"prompt_number": 4
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"To change parameters you can edit params.txt in any text editor. Here to automate things I use the script below."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"sed -i '/## 7. /c\\2 ## 7. N processors... ' params.txt\n",
"sed -i '/## 10. /c\\.85 ## 10. lowered clust thresh... ' params.txt\n",
"sed -i '/## 14. /c\\c85m4p3 ## 14. outprefix... ' params.txt\n",
"sed -i '/## 24./c\\8 ## 24. maxH raised ... ' params.txt\n",
"sed -i '/## 30./c\\* ## 30. all output formats... ' params.txt"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Let's have a look at the changes:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"cat params.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"==** parameter inputs for pyRAD version 3.0a **========================== affected step ==\n",
"./ ## 1. Working directory (all)\n",
"./*.fastq.gz ## 2. Loc. of non-demultiplexed files (if not line 16) (s1)\n",
"./*.barcodes ## 3. Loc. of barcode file (if not line 16) (s1)\n",
"vsearch ## 4. command (or path) to call vsearch (or usearch) (s3,s6)\n",
"muscle ## 5. command (or path) to call muscle (s3,s7)\n",
"TGCAG ## 6. Restriction overhang (e.g., C|TGCAG -> TGCAG) (s1,s2)\n",
"2 ## 7. N processors... \n",
"6 ## 8. Mindepth: min coverage for a cluster (s4,s5)\n",
"4 ## 9. NQual: max # sites with qual < 20 (line 18) (s2)\n",
".85 ## 10. lowered clust thresh... \n",
"rad ## 11. Datatype: rad,gbs,ddrad,pairgbs,pairddrad,merge (all)\n",
"4 ## 12. MinCov: min samples in a final locus (s7)\n",
"3 ## 13. MaxSH: max inds with shared hetero site (s7)\n",
"c85m4p3 ## 14. outprefix... \n",
"==== optional params below this line =================================== affected step ==\n",
" ## 15.opt.: select subset (prefix* only selector) (s2-s7)\n",
" ## 16.opt.: add-on (outgroup) taxa (list or prefix*) (s6,s7)\n",
" ## 17.opt.: exclude taxa (list or prefix*) (s7)\n",
" ## 18.opt.: loc. of de-multiplexed data (s2)\n",
" ## 19.opt.: maxM: N mismatches in barcodes (def= 1) (s1)\n",
" ## 20.opt.: phred Qscore offset (def= 33) (s2)\n",
" ## 21.opt.: filter: def=0=NQual 1=NQual+adapters. 2=strict (s2)\n",
" ## 22.opt.: a priori E,H (def= 0.001,0.01, if not estimated) (s5)\n",
" ## 23.opt.: maxN: max Ns in a cons seq (def=5) (s5)\n",
"8 ## 24. maxH raised ... \n",
" ## 25.opt.: ploidy: max alleles in cons seq (def=2;see docs) (s4,s5)\n",
" ## 26.opt.: maxSNPs: (def=100). Paired (def=100,100) (s7)\n",
" ## 27.opt.: maxIndels: within-clust,across-clust (def. 3,99) (s3,s7)\n",
" ## 28.opt.: random number seed (def. 112233) (s3,s6,s7)\n",
" ## 29.opt.: trim overhang left,right on final loci, def(0,0) (s7)\n",
"* ## 30. all output formats... \n",
" ## 31.opt.: call maj. consens if depth < stat. limit (def=0) (s5)\n",
" ## 32.opt.: keep trimmed reads (def=0). Enter min length. (s2)\n",
" ## 33.opt.: max stack size (int), def= max(500,mean+2*SD) (s3)\n",
" ## 34.opt.: minDerep: exclude dereps with <= N copies, def=1 (s3)\n",
" ## 35.opt.: use hierarchical clustering (def.=0, 1=yes) (s6)\n",
" ## 36.opt.: repeat masking (def.=1='dust' method, 0=no) (s3,s6)\n",
" ## 37.opt.: vsearch threads per job (def.=6; see docs) (s3,s6)\n",
"==== optional: list group/clade assignments below this line (see docs) ==================\n"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"-------------- \n",
"\n",
"__Let's take a look at what the raw data look like.__"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Your input data will be in fastQ format, usually ending in .fq or .fastq. Your data could be split among multiple files, or all within a single file (de-multiplexing goes much faster if they happen to be split into multiple files). The file/s may be compressed with gzip so that they have a .gz ending, but they do not need to be. The location of these files should be entered on line 2 of the params file. Below are the first three reads in the example file."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"less simRADs_R1.fastq.gz | head -n 12 | cut -c 1-90"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"@lane1_fakedata0_R1_0 1:N:0:\n",
"TTTTAATGCAGTGAGTGGCCATGCAATATATATTTACGGGCGCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGCTTAG\n",
"+\n",
"BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB\n",
"@lane1_fakedata0_R1_1 1:N:0:\n",
"TTTTAATGCAGTGAGTGGCCATGCAATATATATTTACGGGCGCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGCTTAG\n",
"+\n",
"BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB\n",
"@lane1_fakedata0_R1_2 1:N:0:\n",
"TTTTAATGCAGTGAGTGGCCATGCAATATATATTTACGGGCGCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGCTTAG\n",
"+\n",
"BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB\n"
]
}
],
"prompt_number": 7
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"------------ \n",
"\n",
"Each read takes four lines. The first is the name of the read (its location on the plate). The second line contains the sequence data. The third line is a spacer. And the fourth line the quality scores for the base calls. In this case arbitrarily high since the data were simulated. \n",
"\n",
"These are 100 bp single-end reads prepared as RADseq. The first six bases form the barcode and the next five bases (TGCAG) the restriction site overhang. All following bases make up the sequence data. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---------------- \n",
"\n",
"## Step 1: de-multiplexing ##"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This step uses information in the barcodes file to sort data into a separate file for each sample. Below is the barcodes file, with sample names and their barcodes each on a separate line with a tab between them."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"cat simRADs.barcodes"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"1A0\tCATCAT\n",
"1B0\tTTTTAA\n",
"1C0\tAGGGGA\n",
"1D0\tTAAGGT\n",
"2E0\tTTTATA\n",
"2F0\tGAGTAT\n",
"2G0\tATAGAG\n",
"2H0\tATGAGG\n",
"3I0\tGGGTTT\n",
"3J0\tTTAAAA\n",
"3K0\tGGATTG\n",
"3L0\tAAGAAG\n"
]
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Step 1 writes the de-multiplexed data to a new file for each sample in a new directory created within the working directory called fastq/."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 1"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\n",
"\tstep 1: sorting reads by barcode\n",
"\t ."
]
}
],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can see that this created a new file for each sample in the directory 'fastq/'"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"ls fastq/"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"1A0_R1.fq.gz\n",
"1B0_R1.fq.gz\n",
"1C0_R1.fq.gz\n",
"1D0_R1.fq.gz\n",
"2E0_R1.fq.gz\n",
"2F0_R1.fq.gz\n",
"2G0_R1.fq.gz\n",
"2H0_R1.fq.gz\n",
"3I0_R1.fq.gz\n",
"3J0_R1.fq.gz\n",
"3K0_R1.fq.gz\n",
"3L0_R1.fq.gz\n"
]
}
],
"prompt_number": 10
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"The statistics for step 1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A new directory called stats will also have been created. Each step of the _pyRAD_ analysis will create a new stats output file in this directory. The stats output for step 1 is below:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"cat stats/s1.sorting.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"file \tNreads\tcut_found\tbar_matched\n",
"simRADs_R1.fastq.gz\t480000\t480000\t480000\n",
"\n",
"\n",
"sample\ttrue_bar\tobs_bars\tN_obs\n",
"3L0 \tAAGAAG \tAAGAAG\t40000 \n",
"1C0 \tAGGGGA \tAGGGGA\t40000 \n",
"2G0 \tATAGAG \tATAGAG\t40000 \n",
"2H0 \tATGAGG \tATGAGG\t40000 \n",
"1A0 \tCATCAT \tCATCAT\t40000 \n",
"2F0 \tGAGTAT \tGAGTAT\t40000 \n",
"3K0 \tGGATTG \tGGATTG\t40000 \n",
"3I0 \tGGGTTT \tGGGTTT\t40000 \n",
"1D0 \tTAAGGT \tTAAGGT\t40000 \n",
"3J0 \tTTAAAA \tTTAAAA\t40000 \n",
"2E0 \tTTTATA \tTTTATA\t40000 \n",
"1B0 \tTTTTAA \tTTTTAA\t40000 \n",
"\n",
"nomatch \t_ \t0\n"
]
}
],
"prompt_number": 11
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Step 2: quality filtering"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This step filters reads based on quality scores, and can be used to detect Illumina adapters in your reads, which is sometimes a problem with homebrew type library preparations. Here the filter is set to the default value of 0, meaning it filters only based on quality scores of base calls. The filtered files are written to a new directory called edits/."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 2"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\tstep 2: editing raw reads \n",
"\t............"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"ls edits/"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"1A0.edit\n",
"1B0.edit\n",
"1C0.edit\n",
"1D0.edit\n",
"2E0.edit\n",
"2F0.edit\n",
"2G0.edit\n",
"2H0.edit\n",
"3I0.edit\n",
"3J0.edit\n",
"3K0.edit\n",
"3L0.edit\n"
]
}
],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The filtered data are written in fasta format (quality scores removed) into a new directory called edits/. Below I show a preview of the file which you can view most easily using the `less` command (I use `head` here to make it fit in the text window better)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"head -n 10 edits/1A0.edit | cut -c 1-80"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
">1A0_0_r1\n",
"TGCAGTGAGTGGCCATGCAATATATATTTACGGGCTCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGC\n",
">1A0_1_r1\n",
"TGCAGTGAGTGGCCATGCAATATATATTTACGGGCTCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGC\n",
">1A0_2_r1\n",
"TGCAGTGAGTGGCCATGCAATATATATTTACGGGCTCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGC\n",
">1A0_3_r1\n",
"TGCAGTGAGTGGCCATGCAATATATATTTACGGGCTCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGC\n",
">1A0_4_r1\n",
"TGCAGTGAGTGGCCATGCAATATATATTTACGGGCTCATAGAGACCCTCAAGACTGCCAACCGGGTGAATCACTATTTGC\n"
]
}
],
"prompt_number": 14
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Step 3: clustering within-samples"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Step 3 de-replicates and then clusters reads within each sample by the set clustering threshold and writes the clusters to new files in a directory called clust.xx"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 3"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\n",
"\tde-replicating files for clustering...\n",
"\n",
"\tstep 3: within-sample clustering of 12 samples at \n",
"\t '.85' similarity. Running 2 parallel jobs\n",
"\t \twith up to6 threads per job. If needed, \n",
"\t\tadjust to avoid CPU and MEM limits\n",
"\n",
"\tsample 1C0 finished, 2000 loci\n",
"\tsample 3J0 finished, 2000 loci\n",
"\tsample 3K0 finished, 2000 loci\n",
"\tsample 1B0 finished, 2000 loci\n",
"\tsample 3L0 finished, 2000 loci\n",
"\tsample 2F0 finished, 2000 loci\n",
"\tsample 3I0 finished, 2000 loci\n",
"\tsample 2H0 finished, 2000 loci\n",
"\tsample 2G0 finished, 2000 loci\n",
"\tsample 2E0 finished, 2000 loci\n",
"\tsample 1A0 finished, 2000 loci\n",
"\tsample 1D0 finished, 2000 loci\n"
]
}
],
"prompt_number": 15
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Once again, I recommend you use the unix command 'less' to look at the clustS files. These contain each cluster separated by \"//\". For the first few clusters below you can see that there is one or two alleles in the cluster and one or a few reads that contained a (simulated) sequencing error. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"less clust.85/1A0.clustS.gz | head -n 26 | cut -c 1-80"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
">1A0_2540_r1;size=17;\n",
"TGCAGTGTAACGTTGTATCCATCGAGTCGATCATAGCCTAAAATAAGTAACACTAATCAGGCGCGCTGGTTGGGGGATCA\n",
">1A0_2541_r1;size=1;+\n",
"TGCAGTGTAACGTTGTATCCAACGAGTCGATCATAGCCTAAAATAAGTAACACTAATCAGGCGCGCTGGTTGGGGGATCA\n",
">1A0_2549_r1;size=1;+\n",
"TGCAGTGTAACGTTGTATCCATCGAGTCGATCATAGCCTAAAATAAGTAACGCTAATCAGGCGCGCTGGTTGGGGGATCA\n",
">1A0_2551_r1;size=1;+\n",
"TGCAGTGTAACGTTGTATCCATCGAGTCGATCATAGCCTAAAATAAGTAACACTAATCAGGCGCGTTGGTTGGGGGATCA\n",
"//\n",
"//\n",
">1A0_2140_r1;size=19;\n",
"TGCAGCTCCGTCACTGCTCAGCGAACCTACTATCTAGTCGGAAAAGGTTCCGGCCCTTATGCTAAGTGCAAGCTGCCAGT\n",
">1A0_2155_r1;size=1;+\n",
"TGCAGCTCCCTCACTGCTCAGCGAACCTACTATCTAGTCGGAAAAGGTTCCGGCCCTTATGCTAAGTGCAAGCTGCCAGT\n",
"//\n",
"//\n",
">1A0_8280_r1;size=10;\n",
"TGCAGCGTATATGATCAGAACCGGGTGAGTGGGTACCGCGAACCGAAAGGCATCGAAAGTTTAGCGCAGCACTAATCTCA\n",
">1A0_8290_r1;size=8;+\n",
"TGCAGCGTATATGATCAGAACCGGGTGAGTGGGTACCGCGAACCGAAAGGCACCGAAAGTTTAGCGCAGCACTAATCTCA\n",
">1A0_8297_r1;size=1;+\n",
"TGCAGCGTATATGATCAGAACCGGGTGAGTGGGAACCGCGAACCGAAAGGCACCGAAAGTTTAGCGCAGCACTAATCTCA\n",
">1A0_8292_r1;size=1;+\n",
"TGCAGCCTATATGATCAGAACCGGGTGAGTGGGTACCGCGAACCGAAAGGCACCGAAAGTTTAGCGCAGCACTAATCTCA\n",
"//\n",
"//\n"
]
}
],
"prompt_number": 16
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---------------\n",
"\n",
"\n",
"The stats output tells you how many clusters were found, and their mean depth of coverage. It also tells you how many pass your minimum depth setting. You can use this information to decide if you wish to increase or decrease the mindepth before it is applied for making consensus base calls in steps 4 & 5."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"head -n 40 stats/s3.clusters.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"taxa\ttotal\tdpt.me\tdpt.sd\td>5.tot\td>5.me\td>5.sd\tbadpairs\n",
"1A0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"1B0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"1C0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"1D0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"2E0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"2F0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"2G0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"2H0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"3I0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"3J0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"3K0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"3L0\t2000\t20.0\t0.0\t2000\t20.0\t0.0\t0\n",
"\n",
" ## total = total number of clusters, including singletons\n",
" ## dpt.me = mean depth of clusters\n",
" ## dpt.sd = standard deviation of cluster depth\n",
" ## >N.tot = number of clusters with depth greater than N\n",
" ## >N.me = mean depth of clusters with depth greater than N\n",
" ## >N.sd = standard deviation of cluster depth for clusters with depth greater than N\n",
" ## badpairs = mismatched 1st & 2nd reads (only for paired ddRAD data)\n",
"\n",
"HISTOGRAMS\n",
"\n",
" \n",
"sample: 1A0\n",
"bins\tdepth_histogram\tcnts\n",
" :\t0------------50-------------100%\n",
"0 \t 0\n",
"5 \t 0\n",
"10 \t 0\n",
"15 \t 0\n",
"20 \t******************************* 2000\n",
"25 \t 0\n",
"30 \t 0\n",
"35 \t 0\n",
"40 \t 0\n",
"50 \t 0\n",
"100 \t 0\n"
]
}
],
"prompt_number": 19
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Steps 4 & 5: Call consensus sequences"
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Step 4 jointly infers the error-rate and heterozygosity across samples."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 4"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\n",
"\tstep 4: estimating error rate and heterozygosity\n",
"\t............"
]
}
],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"less stats/Pi_E_estimate.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"taxa\tH\tE\n",
"3K0\t0.00135982\t0.00048078\t\n",
"1C0\t0.00134858\t0.00048372\t\n",
"1D0\t0.00135375\t0.00048822\t\n",
"3I0\t0.00129751\t0.00048694\t\n",
"2H0\t0.00133223\t0.00049211\t\n",
"2F0\t0.00135365\t0.0004995\t\n",
"2E0\t0.00126915\t0.00051556\t\n",
"1B0\t0.00149924\t0.00049663\t\n",
"1A0\t0.00136043\t0.00051028\t\n",
"3J0\t0.00144422\t0.0005089\t\n",
"2G0\t0.00138185\t0.00051206\t\n",
"3L0\t0.00143349\t0.00051991\t\n"
]
}
],
"prompt_number": 21
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Step 5 calls consensus sequences using the parameters inferred above, and filters for paralogs."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 5"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\n",
"\tstep 5: creating consensus seqs for 12 samples, using H=0.00137 E=0.00050\n",
"\t............"
]
}
],
"prompt_number": 22
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"The stats output for step 5"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"less stats/s5.consens.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"taxon \tnloci\tf1loci\tf2loci\tnsites\tnpoly\tpoly\n",
"2G0 \t2000\t2000\t2000\t178001\t246\t0.001382\n",
"3L0 \t2000\t2000\t2000\t178003\t255\t0.0014326\n",
"3J0 \t2000\t2000\t2000\t178003\t257\t0.0014438\n",
"1A0 \t2000\t2000\t2000\t178002\t242\t0.0013595\n",
"2E0 \t2000\t2000\t2000\t178002\t226\t0.0012696\n",
"1B0 \t2000\t2000\t2000\t178005\t267\t0.0015\n",
"2F0 \t2000\t2000\t2000\t178002\t241\t0.0013539\n",
"2H0 \t2000\t2000\t2000\t178001\t237\t0.0013315\n",
"3I0 \t2000\t2000\t2000\t178003\t231\t0.0012977\n",
"1D0 \t2000\t2000\t2000\t178002\t241\t0.0013539\n",
"1C0 \t2000\t2000\t2000\t178002\t240\t0.0013483\n",
"3K0 \t2000\t2000\t2000\t178001\t242\t0.0013595\n",
"\n",
" ## nloci = number of loci\n",
" ## f1loci = number of loci with >N depth coverage\n",
" ## f2loci = number of loci with >N depth and passed paralog filter\n",
" ## nsites = number of sites across f loci\n",
" ## npoly = number of polymorphic sites in nsites\n",
" ## poly = frequency of polymorphic sites\n"
]
}
],
"prompt_number": 23
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Step 6: Cluster across samples"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Step 6 clusters consensus sequences across samples. It will print its progress to the screen. This uses 6 threads by default. If you enter 0 for param 37 it will use all available processors. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 6 "
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"vsearch v1.0.3_linux_x86_64, 7.5GB RAM, 4 cores\n",
"https://github.com/torognes/vsearch\n",
"\n",
"\n",
"\tfinished clustering\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\n",
"\tstep 6: clustering across 12 samples at '.85' similarity \n",
"\n",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 0% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 0% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 1% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 1% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 2% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 2% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 3% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 3% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 4% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 4% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 5% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 5% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 6% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 6% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 7% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 7% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 8% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 8% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 9% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 9% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 10% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 10% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 11% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 11% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 12% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 12% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 13% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 13% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 14% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 14% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 15% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 15% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 16% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 16% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 17% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 17% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 18% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 18% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 19% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 19% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 20% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 20% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 21% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 21% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 22% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 22% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 23% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 23% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 24% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 24% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 25% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 25% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 26% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 26% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 27% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 27% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 28% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 28% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 29% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 29% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 30% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 30% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 31% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 31% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 32% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 32% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 33% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 33% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 34% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 34% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 35% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 35% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 36% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 36% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 37% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 37% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 38% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 38% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 39% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 39% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 40% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 40% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 41% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 41% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 42% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 42% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 43% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 43% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 44% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 44% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 45% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 45% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 46% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 46% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 47% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 47% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 48% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 48% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 49% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 49% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 50% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 50% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 51% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 51% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 52% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 52% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 53% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 53% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 54% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 54% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 55% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 55% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 56% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 56% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 57% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 57% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 58% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 58% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 59% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 59% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 60% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 60% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 61% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 61% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 62% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 62% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 63% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 63% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 64% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 64% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 65% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 65% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 66% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 66% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 67% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 67% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 68% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 68% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 69% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 69% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 70% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 70% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 71% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 71% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 72% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 72% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 73% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 73% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 74% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 74% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 75% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 75% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 76% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 76% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 77% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 77% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 78% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 78% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 79% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 79% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 80% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 80% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 81% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 81% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 82% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 82% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 83% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 83% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 84% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 84% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 85% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 85% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 86% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 86% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 87% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 87% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 88% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 88% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 89% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 89% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 90% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 90% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 91% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 91% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 92% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 92% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 93% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 93% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 94% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 94% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 95% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 95% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 96% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 96% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 97% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 97% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 98% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 98% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 99% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 99% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 100% \r",
"Reading file /home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.haplos_ 100%\n",
"2256027 nt in 24000 seqs, min 94, max 96, avg 94\n",
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]
}
],
"prompt_number": 24
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Step 7: Assemble final data sets"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The final step is to output data only for the loci that you want to have included in your data set. This filters once again for potential paralogs or highly repetitive regions, and includes options to minimize the amount of missing data in the output. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"pyRAD -p params.txt -s 7"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\tingroup 1A0,1B0,1C0,1D0,2E0,2F0,2G0,2H0,3I0,3J0,3K0,3L0\n",
"\taddon \n",
"\texclude \n",
"\t\n",
"\tWarning: data set c85m4p3.loci already exists\n",
"\t Skipping re-alignment. Creating extra data formats from the existing file\n",
"\t To create a new .loci file and alignment move/delete c85m4p3.loci or change\n",
"\t the outname prefix in the params file\n",
"\n",
"\twriting nexus file\n",
"\twriting phylip file\n",
"\twriting unlinked SNPs file\n",
"\t + writing full SNPs file\n",
"\t + writing STRUCTURE file\n",
"\t + writing geno file\n",
"\t ** must enter group/clade assignments for treemix output \n",
"\twriting vcf file\n",
"\twriting alleles file\n",
"\t ** must enter group/clade assignments for migrate-n output \n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n"
]
}
],
"prompt_number": 26
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Final stats output"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash\n",
"less stats/c85m4p3.stats"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
"2000 ## loci with > minsp containing data\n",
"2000 ## loci with > minsp containing data & paralogs removed\n",
"2000 ## loci with > minsp containing data & paralogs removed & final filtering\n",
"\n",
"## number of loci recovered in final data set for each taxon.\n",
"taxon\tnloci\n",
"1A0\t2000\n",
"1B0\t2000\n",
"1C0\t2000\n",
"1D0\t2000\n",
"2E0\t2000\n",
"2F0\t2000\n",
"2G0\t2000\n",
"2H0\t2000\n",
"3I0\t2000\n",
"3J0\t2000\n",
"3K0\t2000\n",
"3L0\t2000\n",
"\n",
"\n",
"## nloci = number of loci with data for exactly ntaxa\n",
"## ntotal = number of loci for which at least ntaxa have data\n",
"ntaxa\tnloci\tsaved\tntotal\n",
"1\t-\n",
"2\t-\t\t-\n",
"3\t-\t\t-\n",
"4\t0\t*\t2000\n",
"5\t0\t*\t2000\n",
"6\t0\t*\t2000\n",
"7\t0\t*\t2000\n",
"8\t0\t*\t2000\n",
"9\t0\t*\t2000\n",
"10\t0\t*\t2000\n",
"11\t0\t*\t2000\n",
"12\t2000\t*\t2000\n",
"\n",
"\n",
"## var = number of loci containing n variable sites.\n",
"## pis = number of loci containing n parsimony informative var sites.\n",
"n\tvar\tPIS\n",
"0\t41\t551\n",
"1\t1083\t699\n",
"2\t945\t475\n",
"3\t637\t187\n",
"4\t367\t69\n",
"5\t182\t13\n",
"6\t59\t3\n",
"7\t18\t2\n",
"8\t12\t1\n",
"9\t1\t0\n",
"total var= 7848\n",
"total pis= 2591\n",
"sampled unlinked SNPs= 1959\n",
"sampled bi-allelic SNPs= 1911\n",
"sampled unlinked SNPs= 1959\n",
"sampled bi-allelic SNPs= 1911\n"
]
}
],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"--------------- \n",
"\n",
"## Output formats ##"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We created 11 output files from our analysis. The standard two (.loci and .excluded_loci), as well as the 9 additional ones listed in the params file. These are all shown below."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"ls outfiles/"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"c85m4p3.alleles\n",
"c85m4p3.excluded_loci\n",
"c85m4p3.geno\n",
"c85m4p3.loci\n",
"c85m4p3.nex\n",
"c85m4p3.phy\n",
"c85m4p3.snps\n",
"c85m4p3.str\n",
"c85m4p3.unlinked_snps\n",
"c85m4p3.vcf\n"
]
}
],
"prompt_number": 28
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Loci format \n",
"The \".loci\" file contains each locus listed in a fasta-like format that also shows which sites are variable below each locus. Autapomorphies are listed as '-' and shared SNPs as '*'. This is a custom format that is human readable and also used as input to perform D-statistic tests in pyRAD. This is the easiest way to visualize your results. I recommend viewing the file with the command `less`. Below I use a head and cut to make it easy to view in this window."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 39 outfiles/c85m4p3.loci | cut -c 1-75"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
">1A0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGCGATCCTAGTTATCATAAG\n",
">1B0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">1C0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">1D0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">2E0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">2F0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">2G0 TCTCTCTCGCGATCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">2H0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
">3I0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAG\n",
">3J0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAG\n",
">3K0 TCTCTCTCGCGGTCGATGATCTTGCGAGGGAAGTAGCAGGCCAAATCGAGATACTAGTTATCATAAG\n",
">3L0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAG\n",
"// - - * * - * \n",
">1A0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">1B0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">1C0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">1D0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">2E0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">2F0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">2G0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">2H0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">3I0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">3J0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAASTAATGTAAAGGCAC\n",
">3K0 GTTCTGGACAASACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAC\n",
">3L0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAM\n",
"// - - -\n",
">1A0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">1B0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">1C0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">1D0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">2E0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">2F0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">2G0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">2H0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">3I0 TCCGATAGCCAGGACTCGAGGTCGACTACCGGCGTGATGTCGGGTTCACCCCCCGAGCATCGGTGCG\n",
">3J0 TCCGATAGCCAGGACTCGAGGTCGACTACCGGCGTGATGTCGGGTTCACCCCCCGGGCATCGGTGCG\n",
">3K0 TCCGATAGCCAGGACTCGAGGTCGACTACCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
">3L0 TCCGATAGCCAGGACTCGAGGTCGACTACCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCG\n",
"// * * * - \n"
]
}
],
"prompt_number": 29
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### PHY format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 50 outfiles/c85m4p3.phy | cut -c 1-85"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"12 178083\n",
"1A0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGCGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"1B0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"1C0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"1D0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"2E0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"2F0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"2G0 TCTCTCTCGCGATCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"2H0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n",
"3I0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTGAT\n",
"3J0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTGAT\n",
"3K0 TCTCTCTCGCGGTCGATGATCTTGCGAGGGAAGTAGCAGGCCAAATCGAGATACTAGTTATCATAAGAATCTTATTGAK\n",
"3L0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTGAT\n"
]
}
],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### NEX format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 50 outfiles/c85m4p3.nex | cut -c 1-85"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"#NEXUS\n",
"BEGIN DATA;\n",
" DIMENSIONS NTAX=12 NCHAR=178083;\n",
" FORMAT DATATYPE=DNA MISSING=N GAP=- INTERLEAVE=YES;\n",
" MATRIX\n",
" 1B0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 2G0 TCTCTCTCGCGATCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 2F0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 1A0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGCGATCCTAGTTATCATAAGAATCTTATTG\n",
" 2H0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 2E0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 3I0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTG\n",
" 1C0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 3L0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 1D0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
" 3J0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTG\n",
" 3K0 TCTCTCTCGCGGTCGATGATCTTGCGAGGGAAGTAGCAGGCCAAATCGAGATACTAGTTATCATAAGAATCTTATTG\n",
"\n",
" 1B0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 2G0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 2F0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 1A0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 2H0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 2E0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 3I0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 1C0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 3L0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAMGTGTCCAAGGGGATTGAATAC\n",
" 1D0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 3J0 GACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAASTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
" 3K0 SACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGGGGATTGAATAC\n",
"\n",
" 1B0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 2G0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 2F0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 1A0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 2H0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTMCCTA\n",
" 2E0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 3I0 CGACTACCGGCGTGATGTCGGGTTCACCCCCCGAGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 1C0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 3L0 CGACTACCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 1D0 CGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 3J0 CGACTACCGGCGTGATGTCGGGTTCACCCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
" 3K0 CGACTACCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATATGGATACGCCGAGAGTTGCTACCTA\n",
"\n",
" 1B0 GGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGTGCCCGTCAGTGCAGGCGGGCTTAGCTTATTTGAAT\n",
" 2G0 GGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGTGCCCGTCAGTGCAGGCGGGCTTAGCTTATTTGAAT\n",
" 2F0 GGCTAGTTGCGCTATGAGGAGTATACAAGACTTATCTACAGTGCCCGTCAGTGCAGKCGGGCTTAGCTTATTTGAAT\n",
" 1A0 GGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGTGCCCGTCAGTGCAGGCGGGCTTAGCTTATTTGAAT\n",
" 2H0 GGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGTGCCCGTCAGTGCAGGCGGGCTTAGCTTATTTGAAT\n",
" 2E0 GGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGTGCCCGTCAGTGCAGKCGGGCTTAGCTTATTTGAAT\n"
]
}
],
"prompt_number": 31
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Alleles format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 50 outfiles/c85m4p3.alleles| cut -c 1-85"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
">1A0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGCGATCCTAGTTATCATAAGAATCTTATTG\n",
">1A0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGCGATCCTAGTTATCATAAGAATCTTATTG\n",
">1B0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">1B0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">1C0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">1C0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">1D0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">1D0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2E0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2E0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2F0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2F0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2G0_0 TCTCTCTCGCGATCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2G0_1 TCTCTCTCGCGATCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2H0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">2H0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">3I0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTG\n",
">3I0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTG\n",
">3J0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTG\n",
">3J0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGGAGTAGCAGGCCAAACCGAGATACTAGTTATCATAAGAATCTTATTG\n",
">3K0_0 TCTCTCTCGCGGTCGATGATCTTGCGAGGGAAGTAGCAGGCCAAATCGAGATACTAGTTATCATAAGAATCTTATTG\n",
">3K0_1 TCTCTCTCGCGGTCGATGATCTTGCGAGGGAAGTAGCAGGCCAAATCGAGATACTAGTTATCATAAGAATCTTATTG\n",
">3L0_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
">3L0_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTATTG\n",
"// - - * * - * \n",
">1A0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1A0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1B0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1B0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1C0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1C0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1D0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">1D0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2E0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2E0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2F0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2F0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2G0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2G0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2H0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">2H0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3I0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3I0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3J0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAAGTAATGTAAAGGCACGTGTCCAAGG\n",
">3J0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3K0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3K0_1 GTTCTGGACAACACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3L0_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAAGG\n",
">3L0_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCAAGTGTCCAAGG\n",
"// - - - \n"
]
}
],
"prompt_number": 32
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### STRUCTURE (.str) format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 50 outfiles/c85m4p3.str | cut -c 1-20"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"1A0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1A0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1B0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1B0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1C0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1C0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1D0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"1D0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"2E0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"2E0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"2F0 \t\t\t\t\t\t1\t3\t2\t3\t\n",
"2F0 \t\t\t\t\t\t1\t3\t2\t3\t\n",
"2G0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"2G0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"2H0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"2H0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"3I0 \t\t\t\t\t\t3\t3\t0\t1\t\n",
"3I0 \t\t\t\t\t\t3\t3\t0\t1\t\n",
"3J0 \t\t\t\t\t\t3\t3\t2\t1\t\n",
"3J0 \t\t\t\t\t\t3\t3\t2\t1\t\n",
"3K0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"3K0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"3L0 \t\t\t\t\t\t1\t3\t2\t1\t\n",
"3L0 \t\t\t\t\t\t1\t0\t2\t1\t\n"
]
}
],
"prompt_number": 33
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### GENO (.geno) format (used in _Admixture_)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 40 outfiles/c85m4p3.geno "
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"222222220022\n",
"222222222221\n",
"222222220222\n",
"222220222222\n",
"222222220000\n",
"222222221222\n",
"222222222220\n",
"221222222222\n",
"222222022222\n",
"222222220000\n",
"222200000000\n",
"222222220022\n",
"222222212222\n",
"222122222222\n",
"222200000000\n",
"212222222222\n",
"222022222222\n",
"222222212222\n",
"222222122222\n",
"222200000000\n",
"222222022222\n",
"222222200000\n",
"222222220000\n",
"222200000000\n",
"220222222222\n",
"222222221222\n",
"222222202222\n",
"222200022222\n",
"222200000000\n",
"222222212222\n",
"222222202222\n",
"222222212222\n",
"221222222222\n",
"221222222222\n",
"212222222222\n",
"222222202222\n",
"222200020000\n",
"222221222222\n",
"220222222222\n",
"222222022222\n"
]
}
],
"prompt_number": 34
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### SNPs format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 50 outfiles/c85m4p3.snps | cut -c 1-85"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"## 12 taxa, 2000 loci, 7888 snps\n",
"1A0 GAATCCT GCC TTAG AATTAT GTGYTGA GC TAYC CT AGTACC CCC AATC GAAC TCGT GCA TTC CG\n",
"1B0 GAATACT GCC TTAG AATTAT GTGYTGA GC TATC CT AGTTCC CCC AATC GAAC TCGW GCA TTC CS\n",
"1C0 GAATACT GCC TTAG AATTAT GTGTTGA GC TATC CY AGTACC CCC WATC GAAC TCGA GCA TTC CG\n",
"1D0 GAATACT GCC TTAG AATTAT GTGCTGA GC TATT CT ATTACC CCC AATC GAAC GCGA GCM TTC CG\n",
"2E0 GAATACT GCC TTAG AATTAT KTGCTGA GC TATC CT AGTACC CTC AATG GAAC TCGA GCA ATC GG\n",
"2F0 GAATACT GCC TTAG AATCAT KTGCYGA GC TATC CT AGTACC CTC AATG GAAC TCGA SCA ATC GG\n",
"2G0 AAATACT GCC TTAG AATTAT GTGCTGA GC TATC CT AGGACC CTC AATG GARC TCSA GCA ATC GG\n",
"2H0 GAATACT GCC TTAG MATTAT GTGCTGA GA TATC CT TGTAAC GTC AATG GAAC TYGA GCA ATG GG\n",
"3I0 GAGCAAT GCC AACA AAATAT GGGCTGC SC TATC CT AGTACC CCG ATGG AAAC TCGA GSA ATC CG\n",
"3J0 GAGCAAT GSC AACG ARATAT GGGCTGA GC TATC CT AGTACC CCG ATGG AAAC TCGA GCA ATC CG\n",
"3K0 GCATAAK SCC AAAG AAATAT GGGCTSA GC TWTC TT AGTACC CCG ATGG GGAC TCGA GCA AGC CG\n",
"3L0 GAATACT GCM AAAG AAATCY GGSCTGA GC CATC CT AGTACT CCG ATGG GAAT TCGA GCA ATC CG\n"
]
}
],
"prompt_number": 35
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### UNLINKED_SNPs format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 50 outfiles/c85m4p3.unlinked_snps | cut -c 1-85"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"12 1959\n",
"1A0 TCGTTGTTTCCGCATGCAAATCTCTGGCTGATATCTCKGAATGGTCGCAAACCTTGTTAGATTCRTCCATTACCCATCC\n",
"1B0 TCGTTGTTTCCGCATSCAAATCTCTGGCTGATATYTCGGAAWGGTCGGAMATMTTGTTAGATTCGTCCATTACCCATCC\n",
"1C0 TCGTTGTYTCCGCATGCAAATCTCAGGCTGATMKCTCGGGATGGTCGGAAACCTTATTAGWTTCAYCCATTACCAATCC\n",
"1D0 TCGTTGTTTCCGCMTGGAAATCTCTGGCTGATATCTCGGAATGGTCGGAAACCATGTTAGATTCGTCAATTACCCCGCC\n",
"2E0 TCGTTGTTTCGGCAAGCAACTCTTTGGACGATATCTAGGAATGGTCGGCAACCTAGTTAGACTCGTCCATTCYYCATTC\n",
"2F0 TCGCTGTTTCGGCAAGCAACTCTTTGGACGATATCTAGKAATGGTCGGCAWCCTAGTTAGACTCGTCCATTCTCCATCC\n",
"2G0 TCGTTGTTGCGGCAAGCAMCGCTTTGGACGATATCTAGGACTGSTCCGCAACCTAGTTAGACTCGTCCAYTCCCCATCC\n",
"2H0 TCGTTGTTTCGGYAAGCWACTTTTTGACCSTWATCGCGGAATGGTCGGCAACCTTGTTAGACTCGTCCATTACCCATCC\n",
"3I0 CCATGSTTTGGACAAGCAACTTCTTKGCCGATATCTAGGAATRGAAGGAAACCTTGATAGACTCGTTCCTCACCCATCC\n",
"3J0 CCGTGGTTTGGACAAGCAACTTCTTGGCCGATATCTAGGAATGGTAGGAAACCTTGAKGKACTCGTTCCTCACCCATCC\n",
"3K0 TCGTGGTTTGGGCAAGCAACTTCTTGGCCGATATCTAGGAATGGTAGGAAACCTTGATAGACWSGTTCCTCACCCATCA\n",
"3L0 TMGTGGCTTGGGCAAGCAACTTCTTGGCCGATATCTAGGAATGGTCGGAAACCTTGTTAGACTCGTTCCTCACCCATCC\n"
]
}
],
"prompt_number": 36
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## OTHER FORMATS \n",
"\n",
"You may also produce some more complicated formatting options that involve pooling individuals into groups or populations. This can be done for the \"treemix\" and \"migrate\" outputs, which are formatted for input into the programs _TreeMix_ and _migrate-n_, respectively. Grouping individuals into populations is done with the final lines of the params file as shown below, and similar to the assignment of individuals into clades for hierarchical clustering (see full tutorial). \n",
"\n",
"Each line designates a group, and has three arguments that are separated by space or tab. The first is the group name, the second is the minimum number of individuals that must have data in that group for a locus to be included in the output, and the third is a list of the members of that group. Lists of taxa can include comma-separated names and wildcard selectors, like below. Example:\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"## append group designations to the params file\n",
"echo \"pop1 4 1A0,1B0,1C0,1D0 \" >> params.txt\n",
"echo \"pop2 4 2E0,2F0,2G0,2H0 \" >> params.txt\n",
"echo \"pop3 4 3* \" >> params.txt\n",
"\n",
"## view params file\n",
"cat params.txt"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"==** parameter inputs for pyRAD version 3.0a **========================== affected step ==\n",
"./ ## 1. Working directory (all)\n",
"./*.fastq.gz ## 2. Loc. of non-demultiplexed files (if not line 16) (s1)\n",
"./*.barcodes ## 3. Loc. of barcode file (if not line 16) (s1)\n",
"vsearch ## 4. command (or path) to call vsearch (or usearch) (s3,s6)\n",
"muscle ## 5. command (or path) to call muscle (s3,s7)\n",
"TGCAG ## 6. Restriction overhang (e.g., C|TGCAG -> TGCAG) (s1,s2)\n",
"2 ## 7. N processors... \n",
"6 ## 8. Mindepth: min coverage for a cluster (s4,s5)\n",
"4 ## 9. NQual: max # sites with qual < 20 (line 18) (s2)\n",
".85 ## 10. lowered clust thresh... \n",
"rad ## 11. Datatype: rad,gbs,ddrad,pairgbs,pairddrad,merge (all)\n",
"4 ## 12. MinCov: min samples in a final locus (s7)\n",
"3 ## 13. MaxSH: max inds with shared hetero site (s7)\n",
"c85m4p3 ## 14. outprefix... \n",
"==== optional params below this line =================================== affected step ==\n",
" ## 15.opt.: select subset (prefix* only selector) (s2-s7)\n",
" ## 16.opt.: add-on (outgroup) taxa (list or prefix*) (s6,s7)\n",
" ## 17.opt.: exclude taxa (list or prefix*) (s7)\n",
" ## 18.opt.: loc. of de-multiplexed data (s2)\n",
" ## 19.opt.: maxM: N mismatches in barcodes (def= 1) (s1)\n",
" ## 20.opt.: phred Qscore offset (def= 33) (s2)\n",
" ## 21.opt.: filter: def=0=NQual 1=NQual+adapters. 2=strict (s2)\n",
" ## 22.opt.: a priori E,H (def= 0.001,0.01, if not estimated) (s5)\n",
" ## 23.opt.: maxN: max Ns in a cons seq (def=5) (s5)\n",
"8 ## 24. maxH raised ... \n",
" ## 25.opt.: ploidy: max alleles in cons seq (def=2;see docs) (s4,s5)\n",
" ## 26.opt.: maxSNPs: (def=100). Paired (def=100,100) (s7)\n",
" ## 27.opt.: maxIndels: within-clust,across-clust (def. 3,99) (s3,s7)\n",
" ## 28.opt.: random number seed (def. 112233) (s3,s6,s7)\n",
" ## 29.opt.: trim overhang left,right on final loci, def(0,0) (s7)\n",
"* ## 30. all output formats... \n",
" ## 31.opt.: call maj. consens if depth < stat. limit (def=0) (s5)\n",
" ## 32.opt.: keep trimmed reads (def=0). Enter min length. (s2)\n",
" ## 33.opt.: max stack size (int), def= max(500,mean+2*SD) (s3)\n",
" ## 34.opt.: minDerep: exclude dereps with <= N copies, def=1 (s3)\n",
" ## 35.opt.: use hierarchical clustering (def.=0, 1=yes) (s6)\n",
" ## 36.opt.: repeat masking (def.=1='dust' method, 0=no) (s3,s6)\n",
" ## 37.opt.: vsearch threads per job (def.=6; see docs) (s3,s6)\n",
"==== optional: list group/clade assignments below this line (see docs) ==================\n",
"pop1 4 1A0,1B0,1C0,1D0 \n",
"pop2 4 2E0,2F0,2G0,2H0 \n",
"pop3 4 3* \n"
]
}
],
"prompt_number": 39
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating population output files \n",
"Now if we run _pyRAD_ with the 'm' (migrate) or 't' (treemix) output options, it will create their output files. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"pyRAD -p params.txt -s 7"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\tingroup 1A0,1B0,1C0,1D0,2E0,2F0,2G0,2H0,3I0,3J0,3K0,3L0\n",
"\taddon \n",
"\texclude \n",
"\t\n",
"\tWarning: data set c85m4p3.loci already exists\n",
"\t Skipping re-alignment. Creating extra data formats from the existing file\n",
"\t To create a new .loci file and alignment move/delete c85m4p3.loci or change\n",
"\t the outname prefix in the params file\n",
"\n",
"\twriting nexus file\n",
"\twriting phylip file\n",
"\twriting unlinked SNPs file\n",
"\t + writing full SNPs file\n",
"\t + writing STRUCTURE file\n",
"\t + writing geno file\n",
"\t + writing treemix file\n",
"\t data set reduced for group coverage minimums\n",
"\t pop1 ['1A0', '1B0', '1C0', '1D0'] minimum= 4\n",
"\t pop2 ['2E0', '2F0', '2G0', '2H0'] minimum= 4\n",
"\t pop3 ['3J0', '3I0', '3K0', '3L0'] minimum= 4\n",
"\twriting vcf file\n",
"\twriting alleles file\n",
"\twriting migrate-n file\n",
"\t data set reduced for group coverage minimums\n",
"\t pop1 ['1A0', '1B0', '1C0', '1D0'] minimum= 4\n",
"\t pop2 ['2E0', '2F0', '2G0', '2H0'] minimum= 4\n",
"\t pop3 ['3J0', '3I0', '3K0', '3L0'] minimum= 4\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"\n",
"\n",
" ------------------------------------------------------------\n",
" pyRAD : RADseq for phylogenetics & introgression analyses\n",
" ------------------------------------------------------------\n",
"\n",
"\n",
"\tCluster input file: using \n",
"\t/home/deren/Dropbox/Public/PYRAD_TUTORIALS/tutorial_RAD/clust.85/cat.clust_.gz\n",
"\n"
]
}
],
"prompt_number": 40
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## TREEMIX format"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"less outfiles/c85m4p3.treemix.gz | head -n 30"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"pop1 pop2 pop3\n",
"8,0 8,0 4,4\n",
"8,0 8,0 7,1\n",
"8,0 8,0 6,2\n",
"8,0 6,2 8,0\n",
"8,0 8,0 0,8\n",
"8,0 8,0 7,1\n",
"8,0 8,0 6,2\n",
"7,1 8,0 8,0\n",
"8,0 6,2 8,0\n",
"8,0 8,0 0,8\n",
"0,8 8,0 8,0\n",
"8,0 8,0 4,4\n",
"8,0 7,1 8,0\n",
"7,1 8,0 8,0\n",
"0,8 8,0 8,0\n",
"7,1 8,0 8,0\n",
"6,2 8,0 8,0\n",
"8,0 7,1 8,0\n",
"8,0 7,1 8,0\n",
"0,8 8,0 8,0\n",
"8,0 6,2 8,0\n",
"8,0 6,2 0,8\n",
"8,0 8,0 0,8\n",
"0,8 8,0 8,0\n",
"6,2 8,0 8,0\n",
"8,0 8,0 7,1\n",
"8,0 6,2 8,0\n",
"8,0 2,6 8,0\n",
"0,8 8,0 8,0\n"
]
}
],
"prompt_number": 41
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## MIGRATE-n FORMAT"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%%bash \n",
"head -n 40 outfiles/c85m4p3.migrate | cut -c 1-85"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"3 2000 ( npops nloci for data set c85m4p3.loci )\n",
"89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 8\n",
"4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4\n",
"pop1_0 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGCGATCCTAGTTATCATAAGAATCTTAT\n",
"pop1_1 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTAT\n",
"pop1_2 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTAT\n",
"pop1_3 TCTCTCTCGCGGTCGATGATATTGCGAGGGAAGTAGCAGGCCAAATCGAGATCCTAGTTATCATAAGAATCTTAT\n",
"pop1_0 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAA\n",
"pop1_1 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAA\n",
"pop1_2 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAA\n",
"pop1_3 GTTCTGGACAAGACAATAGCTCTCCTCCTATGTATGGCTGCCTGTCACTTAACTAATGTAAAGGCACGTGTCCAA\n",
"pop1_0 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATAT\n",
"pop1_1 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATAT\n",
"pop1_2 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATAT\n",
"pop1_3 TCCGATAGCCAGGTCTCGAGGTCGACTTCCGGCGTGATGTCGGGTTCAACCCCCGGGCATCGGTGCGAAGGATAT\n",
"pop1_0 TTGCTACCTACACACTGAAACGAATATTGCATGGGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGT\n",
"pop1_1 TTGCTACCTACACACTGAAACGAATATTGCATGGGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGT\n",
"pop1_2 TTGCTACCTACACACTGAAACGAATATTGCATGGGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGT\n",
"pop1_3 TTGCTACCTACACACTGAAACGAATATTGCATGGGCTAGTTGTGCTATGAGGAGTATACAAGACTTATCTACAGT\n",
"pop1_0 GCGGGCTTAGCTTATTTGAATACAAATGAATGCACGGTATTGAAYCCCGGCGGGATAAATATTAACAGAATAGCG\n",
"pop1_1 GCGGGCTTAGCTTATTTGAATACAAATGAATGCACGGTATTGAAYCCCGGCGGGATAAATATTAACAGAATAGCG\n",
"pop1_2 GCGGGCTTAGCTTATTTGAATACAAATGAATGCACGGTATTGAATCCCGGCGGGATAAATATTAACAGAATAGCG\n",
"pop1_3 GCGGGCTTAGCTTATTTGAATACAAATGAATGCACGGTATTGAACCCCGGCGGGATAAATATTAACAGAATAGCG\n",
"pop1_0 GTAAAACCCCCGATGCTAACAGCTATTTTAAGCGTGCATTGAGGACGCACCGGACATGTGGTATGTTTCTTTATT\n",
"pop1_1 GTAAAACCCCCGATGCTAACAGCTATTTTAAGCGTGCATTGAGGACGCACCGGACATGTGGTATGTTTCTTTATT\n",
"pop1_2 GTAAAACCCCCGATGCTAACAGCTATTTTAAGCGTGCATTGAGGACGCACCGGACATGTGGTATGTTTCTTTATT\n",
"pop1_3 GTAAAACCCCCGATGCTAACAGCTATTTTAAGCGTGCATTGAGGACGCACCGGACATGTGGTATGTTTCTTTATT\n",
"pop1_0 TTTGTGTTAACCGCCCTTTGCTTTGATATTGCCCGCCAAGCGTCTATTGGCAATYCAGAAGGCTATCAAACGTCT\n",
"pop1_1 TTTGTGTTAACCGCCCTTTGCTTTGATATTGCCCGCCAAGCGTCTATTGGCAATTCAGAAGGCTATCAAACGTCT\n",
"pop1_2 TTTGTGTTAACCGCCCTTTGCTTTGATATTGCCCGCCAAGCGTCTATTGGCAATTCAGAAGGCTATCAAACGTCT\n",
"pop1_3 TTTGTGTTAACCGCCCTTTGCTTTGATATTGCCCGCCAAGCGTCTATTGGCAATTCAGAAGGTTATCAAACGTCT\n",
"pop1_0 CGATTCAATCGATTAGATCTTGGAGTTAAATCACAACACCTGATGTCCTTCAAATAATAGATACGGCCCTATCGC\n",
"pop1_1 CGATTCAATCGATTAGATCTTGGAGTTAAATCACAACACCTGATGTCCTTCAAATAATAGATACGGCCCTATCGC\n",
"pop1_2 CGATTCAATCGATTAGATCTTGGAGTTAAATCACAACACCTGATGTCCTTCAAATAATAGATACGGCCCTATCGC\n",
"pop1_3 CGATTCAATCGATTAGATCTTGGAGTTAAATCACAACACCTGATGTCCTTCAAATAATAGATACGGCCCTATCGC\n",
"pop1_0 GGGACCAAGCTAAAGGTACCGACTCGAGCTGTGGCGTCACTGACAAGTGGCGCAAATATGGTTAGAATGGCGTCG\n",
"pop1_1 GGGACCAAGCTAAAGGTACCGACTCGAGCTGTGGCGTCACTGACTAGTGGCGCAAATATGGTTAGAATGGCGTCG\n",
"pop1_2 GGGACCAAGCTAAAGGTACCGACTCGAGCTGTGGCGTCACTGACAAGTGGCGCAAATATGGTTAGAATGGCGTCG\n",
"pop1_3 GGGACCAAGCTAAATGTACCGACTCGAGCTGTGGCGTCACTGACAAGTGGCGCAAATATGGTTAGAATGGCGTCG\n",
"pop1_0 GGCGCGGTTTGTTTTTCGCAAGGCACCATGTGCCGAATTAATCCTAGTTCTGTGCTAGAACGGTGGATGCCCATT\n"
]
}
],
"prompt_number": 42
}
],
"metadata": {}
}
]
}
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