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天真的我准备把全部流程迁移到GATK4

生信技能树 生信技能树 2022-06-07

我在生信技能树上面发布的GATK4教程也有不少了

GATK4的gvcf流程

GATK4的CNV流程-hg38

你以为的可能不是你以为的

新鲜出炉的GATK4培训教材全套PPT,赶快下载学习吧

曾老湿最新私已:GATK4实战教程

本着尽量使用最新版软件的原则,也准备把之前的gatk对RNA-seq数据找变异的流程进行转换:

$GATK  --java-options "-Xmx25G -Djava.io.tmpdir=./" AddOrReplaceReadGroups \
    -I $id -O ${sample}_right.bam -SO coordinate -ID ${sample}  -LB rna \
    -PL illumina -PU hiseq  -SM ${sample}

    $GATK  --java-options "-Xmx25G -Djava.io.tmpdir=./"  MarkDuplicates \
    -I ${sample}_right.bam -O ${sample}_marked.bam -M $sample.metrics --REMOVE_DUPLICATES TRUE

    $GATK  --java-options "-Xmx25G -Djava.io.tmpdir=./"  FixMateInformation \
    -I ${sample}_marked.bam -O ${sample}_marked_fixed.bam  -SO coordinate 

    $GATK  --java-options "-Xmx25G -Djava.io.tmpdir=./"  SplitNCigarReads \
    -R $GENOME  -I ${sample}_marked_fixed.bam  -O ${sample}_marked_fixed_split.bam \
    -rf ReassignOneMappingQuality -RMQF 255 -RMQT 60 -U ALLOW_N_CIGAR_READS

    #--fix_misencoded_quality_scores
    ## --fix_misencoded_quality_scores only if phred 64

但是走到了 SplitNCigarReads 才发现,这个命令当初学的太久了,忘记各个参数啥意思了,就想搜索看看如何转换。

还真发现了有人问同样的问题,GATK4: How to reassign STAR mapping quality from 255 to 60 with SplitNCigarReads ,而且GATK4开发团队也回答了:EDIT: Geraldine responded here.

但是这是一个否定回答,开发团队让我们回去用GATK3来跑流程。

One risk that I see is that using the STAR --outSAMmapqUnique 60 option maybe fixes the issue with GATK, but that other downstream tools maybe still depend on the (still default) STAR mapping quality value of 255 (e.g. cufflinks).

The mapping quality MAPQ (column 5) is 255 for uniquely mapping reads, and int(-10*log10(1-
1/Nmap)) for multi-mapping reads. This scheme is same as the one used by TopHat and is com-
patible with Cuffinks. The default MAPQ=255 for the unique mappers maybe changed with
--outSAMmapqUnique parameter (integer 0 to 255) to ensure compatibility with downstream tools
such as GATK.

https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf

好吧,回去就回去,gatk3代码是:

module load java/1.8.0_91 
GATK=/home/jianmingzeng/biosoft/GATK/GenomeAnalysisTK.jar
PICARD=/home/jianmingzeng/biosoft/picardtools/2.9.2/picard.jar 
GENOME=/home/jianmingzeng/biosoft/GATK/resources/bundle/hg38/Homo_sapiens_assembly38.fasta
INDEX=/home/jianmingzeng/biosoft/GATK/resources/bundle/hg38/bwa_index/gatk_hg38 
DBSNP=/home/jianmingzeng/biosoft/GATK/resources/bundle/hg38/dbsnp_146.hg38.vcf.gz
kgSNP=/home/jianmingzeng/biosoft/GATK/resources/bundle/hg38/1000G_phase1.snps.high_confidence.hg38.vcf.gz
kgINDEL=/home/jianmingzeng/biosoft/GATK/resources/bundle/hg38/Mills_and_1000G_gold_standard.indels.hg38.vcf.gz

TMPDIR=/home/jianmingzeng/tmp/software
## samtools and bwa are in the environment
## samtools Version: 1.3.1 (using htslib 1.3.1)
## bwa Version: 0.7.15-r1140
cat $1 |while read id
do
    echo $id
    file=$(basename $id )
    sample=${file%%_*}
    echo $sample
    java -Djava.io.tmpdir=$TMPDIR    -Xmx25g -jar $PICARD  AddOrReplaceReadGroups \
    I=$id O=${sample}.bam SO=coordinate RGID=${sample}  RGLB=rna \
    RGPL=illumina RGPU=hiseq  RGSM=${sample}
    java -Djava.io.tmpdir=$TMPDIR    -Xmx25g -jar $PICARD MarkDuplicates \
    INPUT=${sample}.bam OUTPUT=${sample}_marked.bam METRICS_FILE=$sample.metrics REMOVE_DUPLICATES=TRUE
    java -Djava.io.tmpdir=$TMPDIR    -Xmx25g -jar $PICARD FixMateInformation \
    INPUT=${sample}_marked.bam OUTPUT=${sample}_marked_fixed.bam SO=coordinate

    samtools index ${sample}_marked_fixed.bam
    java -Djava.io.tmpdir=$TMPDIR   -Xmx25g -jar $GATK -T SplitNCigarReads \
    -R $GENOME  -I ${sample}_marked_fixed.bam  -o ${sample}_marked_fixed_split.bam \
    -rf ReassignOneMappingQuality -RMQF 255 -RMQT 60 -U ALLOW_N_CIGAR_READS
    #--fix_misencoded_quality_scores
    ## --fix_misencoded_quality_scores only if phred 64
    java -Djava.io.tmpdir=$TMPDIR   -Xmx25g -jar $GATK -T HaplotypeCaller  \
    -R $GENOME -I ${sample}_marked_fixed_split.bam --dbsnp $DBSNP  \
    -stand_emit_conf 10 -o  ${sample}_raw.vcf
    rm ${sample}.bam ${sample}_marked.bam ${sample}_marked_fixed.bam ${sample}_marked_fixed_split.bam
done

纯干货代码,谁学谁获益。

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