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Hi,

As I know GATK is worked fine for Genome SNP Calling. Can I know it work well for Transcriptome SNP calling as well? I can't find much info regarding Transcriptome SNP calling.

If yes, can I know the step for Transcriptome SNP calling by GATK is same as what we did for Genome SNP calling? eg. alignment raw read to reference transcriptome, marking/remove PCR duplicates, local realignment around indel and quality score re-calibration (if know dbSNP is available).

Thanks and looking forward to hear from you.

There are 6 comments on this article. To see them or add your own, read this post on the forum

There are 7 comments on this article. To see them or add your own, read this post on the forum

Hi all: I find that among all the work flows of GATK http://www.broadinstitute.org/gatk/guide/topic?name=methods-and-workflows there are no workflows for RNA-seq analysis. I understand that GATK mainly focuses on variant calling, can anyone tell me how to use GATK for RNA-seq analysis?

thanks daniel

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Hi,

I've been trying to get ReduceReads working in a pipeline I've made that incorporates GATK tools to call variants in RNA-seq data. After performing indel realignment and base recalibration I'm trying to use ReduceReads prior to calling variants using Unified Genotyper.

I've been using GATK version 2.3.9. When I try to use ReduceReads on a 1.7Gb .bam file, I need to set aside 100Gb memory to perform the operation for the process to complete (otherwise I'll get an error saying I didn't provide enough memory to run the program and to adjust the maximum heap size using the -Xmx option etc).

The problem isn't that ReduceReads doesn't work - it does, however of the 100Gb I set aside, it uses 80-90Gb of it. This means I can't run more than one job at a time due to the constraints of the machine I'm using etc.

I've been looking through the GATK forum and understand it may be a GATK version issue, though I've tried using GATK 2.5.2 ReduceReads for this step and it still requires 70-80Gb memory.

Can anyone provide any clues as to what I may be doing wrong? or whether I can do something to make it use less memory so I can run multiple jobs simultaneously?

The command I'm using is:

java -Xmx100g -Djava.io.tmpdir=/RAW/javatmp/ -jar /NMC/LCR/GenomeAnalysisTK-2.5-2-gf57256b/GenomeAnalysisTK.jar -T ReduceReads -R /SCRATCH/LCR/BWAIndex_hg19/genome.fa -I out.bam.sorted.bam.readGroups.bam.rmdup.bam.realigned.bam.recalibrated.bam -o out.bam.sorted.bam.readGroups.bam.rmdup.bam.realigned.bam.recalibrated.bam.reducedReads.bam

Thanks in advance,

Alex

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