Dear all
I have a GATK based workflow for my .fq files:
- Trimming and adapter clipping by using Trimmomatic
- Read alignment against reference with Bowtie2 (all defaults)
- Conversion of .bam to .sam and sorting with Samtools
- Then I use GATK AddOrReplaceReadGroups:
java -jar picard.jar AddOrReplaceReadGroups \
I=$file \
O=$outfile \
SORT_ORDER=coordinate \
CREATE_INDEX=true VALIDATION_STRINGENCY=LENIENT \
RGID=unique_arbitrary_value \
RGLB= unique_arbitrary_value \
RGPL=ILLUMINA \
RGPU= unique_arbitrary_value \
RGSM= unique_arbitrary_value
Then GATK MarkDuplicates
java -jar $EBROOTPICARD/picard.jar MarkDuplicates \
I=$file \
O=$file.mkd_dup.bam \
M=$file.mkd_dup.txt
Then samtools index $file.mkd_dup.bam
Then GATK HaplotypeCaller
gatk --java-options "-Xmx4g" HaplotypeCaller \
-R REF.fna \
-I $file.mkd_dup.bam \
-O $file.g.vcf.gz \
-ERC GVCF
What I have found was after filtering out loci with too much missing data etc my remaining combined gzipped vcf file had around only 600 SNP markers out of 20,000 remaining – with the rest being INDELS. This seems far too high a percentage of Indels – can anyone suggest improvements to my pipeline?
Incidentally, I merged my vcf.gz files with VCFtools: vcf-merge $gz | bgzip -c > mge.vcf.gz (gave me around 10million identified loci)
Because merging with GATK: gatk --java-options "-Xmx4g" CombineGVCFs - created a weird file with ALT alleles called only as “<NON_REF>” (i.e. with no accompanying variant call e.g. “C,<NON_REF>”) and all calls for each sample as “./.”
indels
calling
gatk
variant
picard