Hi all,
I know of various software solutions for this problem e.g. Somatic Sniper, JointSNVMix, etc., but having never used any of them, I am curious if any comparisons of their performance exist (peer-reviewed or otherwise).
Thanks in advance.
Perhaps you should read my samtools paper, where I did an experiment on finding rare differences between data from different sources but for the same individual.
In general, my view is as long as read placement is perfect, even naive methods work sufficiently well. Complex methods only give you theoretical comfort in that case. One of hard parts is all kinds of alignment artifacts. SNVMix and another paper published in Bioinformatics last year try to resolve this by machine learning using multiple statistics that may imply alignment errors. I, however, always prefer to tackle a problem directly, if we can, rather than via machine learning. To me, the simplest yet most effective strategy is to use two distinct alignment algorithms, such as bwa and bwa-sw, which have distinct error modes. You only consider mutations shared between the two alignments. False calls will be vastly reduced. Using decoy sequence also helps around centromeres.
Another complication is structural variations, in which I am less experienced. In some sense, false mutations caused by structural variations are still indication of something different between normal and tumor.
In all, I think you do not need to worry about which software to use for detecting somatic mutations - anything reasonable is fine. You should pay more attention to mismapping and structural variations. My sanger colleagues from the Cancer Group would agree with me. They have published many high-profile papers.
In this paper describing the HugeSeq pipeline they compare SNP detection from GATK and SamTools. And, also compare/combine a number of different methods for structural variation detection.
We use varscan and SomaticSniper along with samtools and GATK
Hello, I am novice on SomaticSniper, bam-somaticsniper -q 1 -Q 40 -f ucsc.hg19.fasta ERR031023.bam ERR031024.bam ERR031024.snp.vcf, this is the command line I used to call different snps between one pair of cancer and normal samples. Unfortunately, I got a large number of machine artifact. May you send me your command line of Somaticsniper? Any suggestion is appreciated.
I think you can now hand Samtools the tumor:normal data together. Also SNVer is worth a look. It uses a different model than Samtools.
You could try these guys software http://www.realtimegenomics.com/Applications/Sequence-Analysis/Cancer-Research I've used there other tools (mapping, variant calling etc) in my work with Bovine sequence data but have not had any reason/chance to try out there tumor/control tools. I
f their tumor tool is anything like their other tools it should be very fast and rather sensitive. They're a free research license available which should be suitable for most researchers.
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version 2.3.6
This paper used validation data to compare popular somatic SNV callers:
Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers
You can also use freebayes to call them. Specify --pooled-discrete and --genotype-qualities, call germline/somatic at the same time, and then pass the result through vcfsamplediff (vcflib).
Virmid paper has been published in Genome Biology. Please enjoy. http://genomebiology.com/2013/14/8/R90/abstract
Note: Please read PDF version instead of the html full text. The publication team made a mistake to replace two figures with another :( It will be fixed soon anyway.
Can Virmid call InDels? When I use Virmid, it only give me SNPs. And I didn't see any parameters that can allow me to call InDels.
You'll need to update the link to MuTect. Broad Institute has begun to put portable versions of their tools on Github, like the latest release of MuTect. The Genome Institute at WashU has been using Github for a while, but portable versions of their tools can be found here and here.