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Pipeline template template » History » Version 18

Bryan Cosca, 06/10/2015 03:09 PM

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h1. Pipeline template template
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h2. Run-Command Template
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<pre>
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  "NAME":{
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   "script_version":"29009a1c1f8a9653042c5853832881aca4141cf2",
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   "repository":"arvados",
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   "script":"run-command",
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   "script_parameters":{
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    "input":{
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     "output_of":"OUTPUT_OF_PREVIOUS_JOB_NAME"
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    },
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    "reference":{
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     "dataclass":"Collection",
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     "default":"3514b8e5da0e8d109946bc809b20a78a+5698",
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     "link_name":"human_g1k_v37 reference data",
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     "title":"NAME Input Reference genome (FASTA)"
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    },
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    "command":[
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     "java",
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     "-Xmx60g",
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     "-jar",
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     "$(dir $(gatk3))/GenomeAnalysisTK.jar",
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     "-T",
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     "PrintReads",
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     "-R",
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     "$(glob $(dir $(reference))/*.fasta)",
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     {
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      "foreach":"iterator",
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      "command":[
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       "-I",
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       "$(iterator)"
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      ]
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     },
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     "-BQSR",
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     "$(bqsr_table)",
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     "-nct",
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     "16",
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     "-o",
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     "$(outputname)"
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    ],
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    "outputname":{
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     "value":{
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      "list":"iterator",
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      "index":"0",
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      "command":"$(basename $(iterator)).bqsrCal.bam"
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     }
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    },
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    "bqsr_table":{
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     "value":{
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      "list":"iterator",
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      "index":"0",
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      "command":"$(dir $(bqsr))/$(basename $(basename $(iterator))).recal_data.table"
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     }
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    },
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    "input_dir":"$(dir $(input))",
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    "task.foreach":[
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     "iterator"
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    ],
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    "iterator":{
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     "value":{
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      "group":"input_dir",
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      "regex":"(.*)\\.realigned.bam"
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     }
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    },
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    "gatk3":{
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     "dataclass":"Collection",
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     "default":"2e98fdc8e90f4c48a0714b711767c9ce+76",
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     "link_name":"Genome Analysis Toolkit 3.2-2",
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     "title":"NAME Input Version of GATK3 jar"
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    },
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    "dbsnp":{
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     "dataclass":"Collection",
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     "default":"8ac324bfa3dfff1ff81ed34b433869b1+6712",
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     "title":"Single Nucleotide Polymorphism database",
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     "description":"NAME Input DBsnp"
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    }
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   },
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   "runtime_constraints":{
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    "max_tasks_per_node":1,
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    "min_nodes":1,
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    "docker_image":"bcosc/arv-base-java",
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    "arvados_sdk_version":"29009a1c1f8a9653042c5853832881aca4141cf2" 
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   },
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   "output_name":false
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</pre>
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h2. Crunch Script Template Template
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<pre>
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 "NAME":{
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   "script_version":"GIT_BRANCH_NAME",
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   "repository":"GIT_REPO_NAME",
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   "script":"GIT_SCRIPT_NAME",
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   "script_parameters":{
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    "input":{
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     "output_of":"PREVIOUS_JOB_NAME"
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    },
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    "samtools":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"0b5dd5ad3fd555dbb9ef81a027b69dec+18147",
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     "title":"NAME Input Samtools Collection"
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    },
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    "bcftools":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"6a0c51bea360b487aa5c9d130435cd00+14097",
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     "title":"NAME Input BCFtools Collection"
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    },
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    "gatk_jar":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"2e98fdc8e90f4c48a0714b711767c9ce+76",
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     "title":"NAME Input GATK Collection"
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    },
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    "reference":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"3514b8e5da0e8d109946bc809b20a78a+5698",
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     "title":"NAME Input Reference Collection"
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    },
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    "picard":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"0eaa58017c3689414a9e644a2297df5c+165",
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     "title":"NAME Input Picard Collection"
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    },
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    "bedtools_bin":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"b2f86c26e05e7a0686e7f39a86d406bf+34584",
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     "title":"NAME Input Bedtools Collection"
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    },
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    "bed_path":{
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     "required":true,
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     "dataclass":"Collection",
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     "default":"a0e2c5057d64bfb9ce2cdefd46f71b27+516",
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     "title":"NAME Input Bed Collection"
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    },
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    "bwa_bin": {
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     "required": true,
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     "dataclass": "Collection",
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     "default": "39c6f22d40001074f4200a72559ae7eb+5745",
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     "title": "NAME Input BWA Binary"
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    },
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   },
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   "runtime_constraints":{
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    "max_tasks_per_node":1,
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    "min_nodes":1,
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    "docker_image":"bcosc/arv-base-java",
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    "arvados_sdk_version":"749b87143ebb0bdcbe2d49deee9c66f6de9f86dd"
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   },
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   "output_name":false
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  },
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</pre>
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h2. Crunch Script Template
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<pre>
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#!/usr/bin/env python
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import arvados
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import subprocess
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import os
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import sys
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import re
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from arvados.collection import Collection as coll
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import arvados_tools
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import shutil
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arvados_tools.spawn_new_task_per_file('input','.*realigned.bqsrCal.bam$',if_sequence=0, and_end_task=True)
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this_job = arvados.current_job()
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this_task = arvados.current_task()
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tmpdir = arvados.current_task().tmpdir
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input_1 = this_task['parameters']['input_1']
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input_1_path = os.path.join(arvados.get_job_param_mount("input"),input_1)
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tmp_input_1_path = os.path.join(tmpdir,input_1) # If we need to copy to tmpdir
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shutil.copyfile(input_1_path,tmp_input_1_path) # If we need to copy to tmpdir
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</pre> 
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<pre>
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samtools_path = arvados_tools.get_file_path('samtools','^samtools$')
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gatk_path = arvados_tools.get_file_path('gatk_jar','^GenomeAnalysisTK.jar$')
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reference_path = arvados_tools.get_file_path('reference','.*f(ast)?a(.gz)?$')
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dbsnp_path = arvados_tools.get_file_path('dbsnp','^dbsnp.*vcf$')
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bgzip_path = arvados_tools.get_file_path('tabix','^bgzip$')
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tabix_path = arvados_tools.get_file_path('tabix','^tabix$')
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tmp_picard_path = arvados_tools.get_file_path('picard','^picard.jar$')
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# Copy picard over to tmpdir because java cannot hand "+" characters
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picard_path = os.path.join(tmpdir,"picard.jar")
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shutil.copyfile(tmp_picard_path,picard_path)
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others:
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bed56Gb37_path = arvados_tools.get_file_path('bed_path','.*bed$')
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</pre>
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<pre>
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gatk_inserttool_args = []
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gatk_inserttool_output_name
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gatk_inserttool_output_path
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gatk_inserttool_pipe = subprocess.check_output()
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</pre>
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<pre>
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samtools_inserttool_args = []
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</pre>
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h2. Script Parameter Template
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h2. Random stuff
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h2. Latest arvados_sdk_version: 
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https://arvados.org/projects/arvados/repository/revisions/master/show/sdk/python
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h2. Random tools I use
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os.path.join(arvados.get_job_param_mount("param"),name)
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h2. Pipe through tools
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bwa_pipe = subprocess.Popen(args,stdout=subprocess.PIPE)
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output_file = open(output_bam_path,'w')
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samtools_pipe = subprocess.Popen(sam_args, stdin=bwa_pipe.stdout, stdout=output_file)
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bwa_pipe.wait()
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samtools_pipe.wait()
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output_file.close()
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h2. Get name of file without n extensions
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base_input_split = re.split('(\.)',input_1)
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base_input_list = base_input_split[0:len(base_input_split)-n*2]
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base_name = ''.join(base_input_list)
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print base_name