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| [ipedroso@jimi log]$ cat bcbio-nextgen-debug.log | |
| [2014-12-17T14:05Z] Resource requests: bwa, sambamba, samtools; memory: 2.00; cores: 16, 1, 16 | |
| [2014-12-17T14:05Z] Configuring 3 jobs to run, using 16 cores each with 32.1g of memory reserved for each job | |
| [2014-12-17T14:05Z] Timing: organize samples | |
| [2014-12-17T14:05Z] multiprocessing: organize_samples | |
| [2014-12-17T14:05Z] Using input YAML configuration: /media/TeraData/ipedroso/ANALYSES/Populus/Diversity_1/populus_trichocarpa_diversity_1/config/populus_trichocarpa_diversity_1.yaml | |
| [2014-12-17T14:05Z] Checking sample YAML configuration: /media/TeraData/ipedroso/ANALYSES/Populus/Diversity_1/populus_trichocarpa_diversity_1/config/populus_trichocarpa_diversity_1.yaml | |
| [2014-12-17T14:05Z] Testing minimum versions of installed programs | |
| [2014-12-17T14:05Z] Timing: alignment preparation | |
| [2014-12-17T14:05Z] multiprocessing: prep_align_inputs |
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| ##fileformat=VCFv4.2 | |
| ##FILTER=<ID=PASS,Description="All filters passed"> | |
| ##samtoolsVersion=1.0+htslib-1.0 | |
| ##samtoolsCommand=samtools mpileup -f /home/ipedroso/APP/bcbio-nextgen/genomes/populus_trichicarpa/ptri_v3/seq/ptri_v3.fa -t DP -u -g -l /media/TeraData/ipedroso/ANALYSES/Populus/Diversity_1/populus_trichocarpa_diversity_1/work/samtools/scaffold_2499/GW-10958-scaffold_2499_0_3827-raw-regions.bed /media/TeraData/ipedroso/ANALYSES/Populus/Diversity_1/populus_trichocarpa_diversity_1/work/align/GW-10958/14_2014-09-26_populus_trichocarpa_diversity_1-sort.bam | |
| ##reference=file:///home/ipedroso/APP/bcbio-nextgen/genomes/populus_trichicarpa/ptri_v3/seq/ptri_v3.fa | |
| ##contig=<ID=Chr01,length=50495391> | |
| ##contig=<ID=Chr02,length=25263035> | |
| ##contig=<ID=Chr03,length=21816808> | |
| ##contig=<ID=Chr04,length=24267051> | |
| ##contig=<ID=Chr05,length=25890704> |
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| import theano | |
| import theano.tensor as T | |
| theano.config.compute_test_value = 'off' | |
| import numpy as np | |
| # routine to make some data up | |
| def makeup_data(n,p): | |
| X = np.memmap('test.memmap', dtype='float64', mode='w+', shape=(n,p)) |
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| import pymc as mc | |
| import numpy as np | |
| import time | |
| import theano.tensor as T | |
| import theano | |
| theano.config.compute_test_value = 'off' | |
| ## generate some data | |
| N = 10000 |
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| structure(list(ensembl = structure(c(11L, 11L, 11L, 11L, 11L, | |
| 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, | |
| 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, | |
| 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 28L, 28L, | |
| 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, 28L, | |
| 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, | |
| 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, | |
| 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, | |
| 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 4L, | |
| 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, |
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