关于python:01GATK人种系变异最佳实践SnakeMake流程WorkFlow简介

45次阅读

共计 2876 个字符,预计需要花费 8 分钟才能阅读完成。

学习的第一个 GATK 找变异流程,人的种系变异的短序列变异,包含 SNP 和 INDEL。写了一个 SnakeMake 剖析流程,从 fastq 文件到最初的 vep 正文后的 VCF 文件,对于 VCF 的介绍能够参考上一篇推文基因序列变异信息 VCF (Variant Call Format)

流程代码在 https://jihulab.com/BioQuest/smkhgs 或 https://github.com/BioQuestX/smkhgs

README

GATK best practices workflow Pipeline summary

SnakeMake workflow for Human Germline short variants (SNP+INDEL)

Reference

  1. Reference genome related files and GTAK budnle files (GATK)
  2. VEP Variarition annotation files (VEP)

Prepare

  1. Adapter trimming (Fastp)
  2. Aligner (BWA mem2)
  3. Mark duplicates (samblaster)
  4. Generates recalibration table for Base Quality Score Recalibration (BaseRecalibrator)
  5. Apply base quality score recalibration (ApplyBQSR)

Quality control report

  1. Fastp report (MultiQC)
  2. Alignment report (MultiQC)

Call

  1. Call germline SNPs and indels via local re-assembly of haplotypes (HaplotypeCaller)
  2. Import VCFs to GenomicsDB (GenomicsDBImport)
  3. Perform joint genotyping on one or more samples pre-called with HaplotypeCaller (GenotypeGVCFs)

Filter

  1. Select a SNP or INDEL of variants from a VCF file (SelectVariants)
  2. Build a recalibration model to score variant quality for filtering purposes (VariantRecalibrator)
  3. Apply a score cutoff to filter variants based on a recalibration table (ApplyVQSR)
  4. Merge all the VCF files (Picard)

Annotation

Annotate variant calls with VEP (VEP)

SnakeMake Report

Outputs

.
├── config
│   ├── captured_regions.bed
│   ├── config.yaml
│   └── samples.tsv
├── dag.svg
├── logs
│   ├── annotate
│   ├── call
│   ├── filter
│   ├── prepare
│   ├── qc
│   ├── ref
│   └── trim
├── raw
│   ├── SRR24443168.fastq.gz
│   └── SRR24443169.fastq.gz
├── README.md
├── report
│   ├── fastp_multiqc_data
│   ├── fastp_multiqc.html
│   ├── prepare_multiqc_data
│   ├── prepare_multiqc.html
│   └── vep_report.html
├── results
│   ├── called
│   ├── filtered
│   ├── prepared
│   ├── trimmed
│   └── vep_annotated.vcf.gz
├── workflow
│   ├── envs
│   ├── report
│   ├── rules
│   ├── schemas
│   ├── scripts
│   └── Snakefile

Directed Acyclic Graph

Reference

GATK best practices workflow: https://gatk.broadinstitute.org/hc/en-us/sections/360007226651-Best-Practices-Workflows
GATK: https://software.broadinstitute.org/gatk/
VEP: https://www.ensembl.org/info/docs/tools/vep/index.html
fastp: https://github.com/OpenGene/fastp
BWA mem2: http://bio-bwa.sourceforge.net/
samblaster: https://github.com/GregoryFaust/samblaster
BaseRecalibrator: https://gatk.broadinstitute.org/hc/en-us/articles/13832708374939-BaseRecalibrator
ApplyBQSR: https://github.com/GregoryFaust/samblaster
HaplotypeCaller: https://gatk.broadinstitute.org/hc/en-us/articles/13832687299739-HaplotypeCaller
GenomicsDBImport: https://gatk.broadinstitute.org/hc/en-us/articles/13832686645787-GenomicsDBImport
GenotypeGVCFs: https://gatk.broadinstitute.org/hc/en-us/articles/13832766863259-GenotypeGVCFs
SelectVariants: https://gatk.broadinstitute.org/hc/en-us/articles/13832694334235-SelectVariants
VariantRecalibrator: https://gatk.broadinstitute.org/hc/en-us/articles/13832694334235-VariantRecalibrator
ApplyVQSR: https://gatk.broadinstitute.org/hc/en-us/articles/13832694334235-ApplyVQSR
Picard: https://broadinstitute.github.io/picard
MultiQC: https://multiqc.info

正文完
 0