终于看到了一个完整的mutect2使用脚本

因为嫌麻烦，所以一直使用的是简化版mutect2流程，其实就一个命令：

time $GATK  --java-options "-Xmx10G -Djava.io.tmpdir=./"  Mutect2 -R $reference \
-I $tumor_bam  -tumor $(basename "$tumor_bam" _recal.bam) \
-I $normal_bam -normal $(basename "$normal_bam" _recal.bam) \
-O ${sample}_mutect2.vcf
$GATK  FilterMutectCalls -V ${sample}_mutect2.vcf -O ${sample}_somatic.vcf

但是很明显，这其实不符合官网教程的理念

https://gatkforums.broadinstitute.org/gatk/discussion/9183/how-to-call-somatic-snvs-and-indels-using-mutect2 https://software.broadinstitute.org/gatk/documentation/article?id=9183

但是官网教程的确太繁琐，里面涉及到6个步骤，而我只是运行了最后一个！

因为种种原因，没能抽出时间细致的探索mutect2的用法，但是无意中搜索到脚本一个： https://figshare.com/articles/scripts_sh/4542397

可以说是非常良心了：

#!/bin/sh

##GATK bundle download
wget ftp://[e-mail]/bundle/hg19/ucsc.hg19.fasta.gz -O /path/to/GATK/bundle/ucsc.hg19.fasta.gz
wget ftp://[e-mail]/bundle/hg19/dbsnp_138.hg19.vcf.gz -O /path/to/GATK/bundle/dbsnp_138.hg19.vcf.gz
wget https://ndownloader.figshare.com/files/7354246 -O /path/to/GATK/bundle/TP53.sorted.bed
wget https://ndownloader.figshare.com/files/7354213 -O /path/to/GATK/bundle/CosmicCodingMuts.chr.sort.head.vcf

##ANNOVAR database files download
export PATH=$PATH:/path/to/annovar

annotate_variation.pl -buildver hg19 -downdb -webfrom annovar refGene humandb/
annotate_variation.pl -buildver hg19 -downdb cytoBand humandb/
annotate_variation.pl -buildver hg19 -downdb genomicSuperDups humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar esp6500siv2_all humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar 1000g2015aug humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar snp138 humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar dbnsfp30a humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar cosmic70 humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar exac03 humandb/
annotate_variation.pl -buildver hg19 -downdb -webfrom annovar clinvar_20160302 humandb/

#define the reference file path
GATK=/path/to/GATK/GenomeAnalysisTK.jar
REF=/path/to/GATK/bundle/ucsc.hg19.fasta
DBSNP=/path/to/GATK/bundle/dbsnp_138.hg19.vcf
COSMIC=/path/to/GATK/bundle/CosmicCodingMuts.chr.sort.head.vcf
BED=/path/to/GATK/bundle/TP53.sorted.bed

#create a Panel of Normals (PoN) vcf file from the 4 low-grade tumour samples
for pathandfile in /path/to/EGA/normal/*.clean.recal.TP53.bam ; do
   basewithpath=${pathandfile%.clean.recal.TP53.*}
   basenopath=$(basename $basewithpath)

java -jar $GATK \
   -T MuTect2 \
   -R $REF \
   -I:tumor $(echo $basewithpath).clean.recal.TP53.bam \
   --dbsnp $DBSNP \
   --cosmic $COSMIC \
   --artifact_detection_mode \
   -L $BED \
   -o $(echo $basewithpath).clean.recal.TP53.normal.vcf
done

java -jar $GATK \
   -T CombineVariants \
   -R $REF \
   -V /path/to/EGA/normal/GB544-10_S18.clean.recal.TP53.normal.vcf -V /path/to/EGA/normal/GB624-11_S81.clean.recal.TP53.normal.vcf -V /path/to/EGA/normal/GB730-12_S41.clean.recal.TP53.normal.vcf -V /path/to/EGA/normal/GB909-13_S90.clean.recal.TP53.normal.vcf \
   -minN 2 \
   --setKey "null" \
   --filteredAreUncalled \
   --filteredrecordsmergetype KEEP_IF_ANY_UNFILTERED \
   -L $BED \
   -o /path/to/EGA/normal/MuTect2_PON.vcf

#call somatic variants
for pathandfile in /path/to/EGA/tumor/*.clean.recal.TP53.bam ; do
   basewithpath=${pathandfile%.clean.recal.TP53.*}
   basenopath=$(basename $basewithpath)
   
java -jar $GATK \
   -T MuTect2 \
   -R $REF \
   --dbsnp $DBSNP \
   --cosmic $COSMIC \
   -dt NONE \
   --input_file:tumor $(echo $basewithpath).clean.recal.TP53.bam \
   --intervals $BED \
   -PON /path/to/EGA/normal/MuTect2_PON.vcf \
   -o $(echo $basewithpath).clean.recal.TP53.vcf

done

#ANNOVAR annotation
mkdir /path/to/EGA/tumor/ANNOVAR
cp /path/to/EGA/tumor/*.vcf /path/to/EGA/tumor/ANNOVAR

##convert file format
for pathandfile in /path/to/EGA/tumor/ANNOVAR/*.vcf ; do
   filename=${pathandfile%.*}
   convert2annovar.pl --format vcf4 --includeinfo --withzyg $pathandfile > $(echo $filename).avinput
done

##add sample information
for pathandfile in /path/to/EGA/tumor/ANNOVAR/*.avinput ; do
   filename=$(basename $pathandfile)
   mainfilename=${filename%.clean.recal.TP53.avinput}
   pathandmain=${pathandfile%.*}
   awk -v var1="$mainfilename" '{OFS = "\t" ; print $0, var1}' $pathandfile > $(echo $pathandmain).avinputs
done

##merge file
cat /path/to/EGA/tumor/ANNOVAR/*.avinputs > /path/to/EGA/tumor/ANNOVAR/TP53.Tonly.avinput
   
##annotate
table_annovar.pl /path/to/EGA/tumor/ANNOVAR/TP53.Tonly.avinput /path/to/annovar/humandb/ -buildver hg19 -out /path/to/EGA/tumor/ANNOVAR/TP53.Tonly -remove -protocol refGene,cytoBand,genomicSuperDups,esp6500siv2_all,1000g2015aug_all,snp138,dbnsfp30a,cosmic70,exac03,clinvar_20160302 -operation g,r,r,f,f,f,f,f,f,f --otherinfo

虽然这个流程是基于 hg19 参考基因组的，但是很容易就能改写为 hg38版本的！

还有一个问题是他那个流程的项目背景是，得到的肿瘤样品是没有配对normal的，而是 create a Panel of Normals (PoN) vcf file from the 4 low-grade tumour samples

而且，这个流程是基于  GATK3成熟版本的，并不是GATK4哦。

如果大家有GATK4的MUTECT2经验，可以交流一下哈。