Question: Using GATK's HaplotypeCaller or Mutect2 for somatic cancer samples with no normal panel
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gravatar for jsneaththompson
12 months ago by
jsneaththompson60 wrote:

As the title says, I'm working on variant calling for somatic variant discovery where I have tumour samples, but no normal samples to compare with.

Previously I've been using GATK's UnifiedGenotyper for variant calling, but as this tool is deprecated, I want to switch to the newer GATK variant calling tools. However, I can't decide whether it would be more appropriate to use HaplotypeCaller or Mutect2.

On the one hand, HaplotypeCaller can be run without requiring a normal sample for comparison, but the documentation for HaplotypeCaller states that:

the algorithms used to calculate variant likelihoods is not well suited to extreme allele frequencies (relative to ploidy) so its use is not recommended for somatic (cancer) variant discovery. For that purpose, use MuTect2 instead.

However, Mutect2 is still in Beta, and although it can be run on tumour samples only, and in the Mutect2 documentation it says:

Tumor-only variant calling is possible but it is NOT supported and we will not answer any questions about it until it becomes a supported feature.

So neither tool is ideal for my purposes, but I'm having trouble deciding which will be the most applicable to my data. Any suggestions or advice would be greatly appreciated.

ADD COMMENTlink modified 12 months ago by Sean Davis25k • written 12 months ago by jsneaththompson60
1

Hi, if you have only tumor sample and have to call somatic variant, then from my own experience Mutect2 is the best choice, and also I evaluated the performance between single sample and paired samples, I think single sample could also identify the positive somatic mutation but can not filter some individual specific germline mutation or some sequencing error.

So, if your main goal is to identify important hotspot mutation in tumor biology, then only tumor sample is somewhat enough by using Mutect2 combined other filter progress such as dbsnp filter ,1000-genome filter and allele frequency , read depth cut-off ,etc. You can try it.

ADD REPLYlink modified 12 months ago • written 12 months ago by Sparrow_kop190
3
gravatar for Sean Davis
12 months ago by
Sean Davis25k
National Institutes of Health, Bethesda, MD
Sean Davis25k wrote:

Some resources that address your question more broadly:

ADD COMMENTlink written 12 months ago by Sean Davis25k
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