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Tingting Gong il y a 3 ans
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      README.md
  2. +8
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      defaults
  3. +13
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      inputs
  4. BIN
      tasks/.DS_Store
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      tasks/manta.wdl
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      workflow.wdl

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README.md Voir le fichier

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# Strelka2

You don't need to tune the parameters of strelka. It bases on [trained models](<https://github.com/Illumina/strelka/blob/v2.9.x/docs/userGuide/trainingGermlineEmpiricalScore.md>), you may train new models to improve performance.





Two steps:

1. Generate the configuration

```bash
```

2. Run Strelka

```bash
```

##### Per sample run time

4h30min

##### Reference

1. Strelka User Guide <https://github.com/Illumina/strelka/blob/v2.9.x/docs/userGuide/README.md>
2. Strelka paper <https://www.nature.com/articles/s41592-018-0051-x>

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defaults Voir le fichier

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{
"fasta": "GRCh38.d1.vd1.fa",
"disk_size": "500",
"cluster_config": "OnDemand bcs.a2.7xlarge img-ubuntu-vpc",
"docker": "registry.cn-shanghai.aliyuncs.com/pgx-docker-registry/sentieon-genomics:v2019.11.28",
"ref_dir": "oss://pgx-reference-data/GRCh38.d1.vd1/",
"memory": "64"
}

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inputs Voir le fichier

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{
"{{ project_name }}.fasta": "{{ fasta }}",
"{{ project_name }}.tumour_bam_index": "{{ tumour_bam_index }}",
"{{ project_name }}.disk_size": "{{ disk_size }}",
"{{ project_name }}.normal_bam_index": "{{ normal_bam_index }}",
"{{ project_name }}.docker": "{{ docker }}",
"{{ project_name }}.tumour_bam": "{{ tumour_bam }}",
"{{ project_name }}.cluster_config": "{{ cluster_config }}",
"{{ project_name }}.normal_bam": "{{ normal_bam }}",
"{{ project_name }}.memory": "{{ memory }}",
"{{ project_name }}.sample": "{{ sample }}",
"{{ project_name }}.ref_dir": "{{ ref_dir }}"
}

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tasks/.DS_Store Voir le fichier


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tasks/manta.wdl Voir le fichier

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task manta {

File ref_dir
File fasta
File normal_bam
File normal_bam_index
File tumour_bam
File tumour_bam_index
String memory
String sample
String docker
String cluster_config
String disk_size

command <<<

nt=$(nproc)
mkdir -p /cromwell_root/tmp

manta_config=opt/manta-1.6.0.centos6_x86_64/bin/configManta.py

$manta_config --normalBam ${normal_bam} --tumorBam ${tumour_bam} --referenceFasta ${ref_dir}/${fasta} --runDir /cromwell_root/tmp

/cromwell_root/tmp/runWorkflow.py -j $nt -g ${memory}

cp /cromwell_root/tmp/results/variants/somaticSV.vcf.gz ${sample}_manta_somaticSV.vcf.gz
cp /cromwell_root/tmp/results/variants/diploidSV.vcf.gz ${sample}_manta_germlineSV.vcf.gz


>>>

runtime {
docker:docker
cluster: cluster_config
systemDisk: "cloud_ssd 40"
dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
}
output {
File manta_somatic_vcf = "${sample}_manta_somaticSV.vcf.gz"
File manta_germline_vcf = "${sample}_manta_germlineSV.vcf.gz"
}
}

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workflow.wdl Voir le fichier

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import "./tasks/manta.wdl" as manta


workflow {{ project_name }} {

File ref_dir
File fasta
File normal_bam
File normal_bam_index
File tumour_bam
File tumour_bam_index
String memory
String sample
String docker
String cluster_config
String disk_size

call manta.manta as manta {
input:
fasta=fasta,
ref_dir=ref_dir,
normal_bam=normal_bam,
normal_bam_index=normal_bam_index,
tumour_bam=tumour_bam,
tumour_bam_index=tumour_bam_index,
memory=memory,
sample=sample,
docker=docker,
cluster_config=cluster_config,
disk_size=disk_size
}
}


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