Software
MutationSeq paper on feature based classifiers for somatic mutation detection published
Jiarui Ding; Ali Bashashati; Andrew Roth; Arusha Oloumi; Kane Tse; Thomas Zeng; Gholamreza Haffari; Martin Hirst; Marco A. Marra; Anne Condon; Samuel Aparicio; Sohrab P. Shah. “Feature based classifiers for somatic mutation detection in tumour-normal paired sequencing data.”
SNVMix
Detecting single nucleotide variants from next generation sequencing data
SNVMix is designed to detect single nucleotide variants from next generation sequencing data. SNVMix is a post-alignment tool. Given a pileup file (either Maq or Samtools format) as input and model parameters, SNVMix will output the probability that each position is one of three genotypes: aa (homozygous for the reference allele, where the reference is the genome the reads were aligned to), ab (heterozygous) and bb (homozygous for a non-reference allele). A tool for fitting the model using expectation maximization is also supplied (use -T option).
Download
The source code implemented in C is available for distribution under an open source license. Supported platforms are Linux and Mac OS X. A working gcc compiler is needed and under Linux libc >= 4.6.27 is required.
Download latest version: SNVMix2-0.11.8-r4.tar.gz.
Changes:
- Fixed a parsing problem present when generating pileups for RNA-Seq data with samtools > 0.1.8.
- Error reporting when number of columns in pileup file is wrong.
Notes for version 0.11.8:
Alpha and beta parameters can now be specified on the command line for training using three new flags:
-a #,#,# Provide alpha training parameters -b #,#,# Provide beta training parameters -d #,#,# Provide delta training parameters
You can also specify training parameters in a space-separated file using:
-M Provide a file containing training parameters
It is also recommended you update to this due to a bug fix. Older versions affected by that bug presented sporadic segmentation faults when dealing with model files.
Installation
> tar -xzvf SNVMix2-0.11.8-r4.tar.gz > cd SNVMix2-0.11.8-r4/ > make > ./SNVMix2 -h
Model parameter file
In the absence of training data, a model file (input with -m) containing the mu and pi parameters of the model derived in the Shah et al , Nature (2009) is provided here:
References:
If you use SNVMix in your work, please cite the following papers:
Sohrab P. Shah, Ryan D. Morin, Jaswinder Khattra, Leah Prentice, Trevor Pugh, Angela Burleigh, Allen Delaney, Karen Gelmon, Ryan Giuliany, Janine Senz, Christian Steidl, Robert A. Holt, Steven Jones, Mark Sun, Gillian Leung, Richard Moore, Tesa Severson, Greg A. Taylor, Andrew E. Teschendorff, Kane Tse, Gulisa Turashvili, Richard Varhol, Rene L. Warren, Peter Watson, Yongjun Zhao, Carlos Caldas, David Huntsman, Martin Hirst, Marco A. Marra and Samuel Aparicio. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature. vol461, 809-813. (2009) [PDF]
Goya R, Sun MG, Morin RD, Leung G, Ha G, Wiegand KC, Senz J, Crisan A, Marra MA, Hirst M, Huntsman D, Murphy KP, Aparicio S, Shah SP. SNVMix: predicting single nucleotide variants from next-generation sequencing of tumors. Bioinformatics . 2010 Mar 15;26(6):730-6. [Link]
Comments and/or questions should be directed to Sohrab Shah <sshah@bccrc.ca> and Rodrigo Goya <rgoya@bcgsc.ca> .
JointSNVMix software released
Description
JointSNVMix implements a probabilistic graphical model to analyse sequence data from tumour/normal pairs. The model draws statistical strength by analysing both genome jointly to more accurately classify germline and somatic mutations.
Latest Release v0.6.0
SNVMix software released
We have released a C implementation of the software used in Shah et al (2009) Nature: “Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution.“. Please click here for more information.
