Detecting single nucleotide variants from next generation sequencing data.

Project Description

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 genotype:  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).


If you use SNVMix in your work, please cite the following paper:

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)

For More Information

The SNVMix software is developed in collaboration with the BC Cancer Research Centre, for more information and the links to download releases of this software, please visit the BCCRC SNVMix software home page.