GVCF 模式

gatk HaplotypeCaller \
    -R output/index/ref.fasta \
    -I output/mapping/mother.sorted.markdup.BQSR.bam \
    -O output/gvcf/mother.sorted.markdup.g.vcf \
    --emit-ref-confidence GVCF \
    -L 20:10,000,000-10,200,000

 gatk GenomicsDBImport \
    -V gs://gatk-tutorials/workshop_1903/2-germline/gvcfs/mother.g.vcf.gz \
    -V gs://gatk-tutorials/workshop_1903/2-germline/gvcfs/father.g.vcf.gz \
    -V gs://gatk-tutorials/workshop_1903/2-germline/gvcfs/son.g.vcf.gz \
    --genomicsdb-workspace-path /home/jupyter-user/2-germline-vd/sandbox/trio \
    --intervals 20:10,000,000-10,200,000

对于那些不能使用 GenomicDBImport 的用户，另一种方法是将 GVCF 与 CombinGVCF 合并。

gatk CombineGVCFs \
    -R output/index/ref.fasta  \
    --variant output/gvcf/mother.sorted.markdup.g.vcf  \
    -O output/gvcf/cohort.g.vcf.gz

因为检查数据库中的数据并不容易，所以我们将使用 SelectVariants 从 GenomicsDB 数据库中提取这三个组合的数据。

gatk SelectVariants \
    -R /home/jupyter-user/2-germline-vd/ref/ref.fasta \
    -V gendb://sandbox/trio \
    -O /home/jupyter-user/2-germline-vd/sandbox/trio_selectvariants.g.vcf

对这三个人进行联合基因分型以产生 VCF

gatk GenotypeGVCFs \
    -R /home/jupyter-user/2-germline-vd/ref/ref.fasta \
    -V gendb://sandbox/trio \
    -O /home/jupyter-user/2-germline-vd/sandbox/trioGGVCF.vcf \
    -L 20:10,000,000-10,200,000

gatk HaplotypeCaller \
    -R ref/ref.fasta \
    -I bams/mother.bam \
    -I bams/father.bam \
    -I bams/son.bam \
    -O sandbox/trio_hcjoint_nq.vcf \
    -L 20:10,000,000-10,200,000 \
    -new-qual \
    -bamout sandbox/trio_hcjoint_nq.ba

gatk --java-options "-Xmx4g" GenotypeGVCFs \
    -R output/index/ref.fasta \
    -V output/gvcf/cohort.g.vcf.gz \
    -O output/gvcf/output.vcf.gz
 
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