Introduction

Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE ( http://bioinformatics.mdanderson.org/main/MuSE ), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.

Publications

  1. MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data.
    Cite this
    Fan Y, Xi L, Hughes DS, Zhang J, Zhang J, Futreal PA, Wheeler DA, Wang W, 2016-08-01 - Genome biology

Credits

  1. Yu Fan
    Developer

    Department of Bioinformatics and Computational Biology - Unit 1410, The University of Texas MD Anderson Cancer Center, United States of America

  2. Liu Xi
    Developer

    Human Genome Sequencing Center, Baylor College of Medicine, United States of America

  3. Daniel S T Hughes
    Developer

    Human Genome Sequencing Center, Baylor College of Medicine, United States of America

  4. Jianjun Zhang
    Developer

    Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, United States of America

  5. Jianhua Zhang
    Developer

    Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, United States of America

  6. P Andrew Futreal
    Developer

    Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, United States of America

  7. David A Wheeler
    Developer

    Human Genome Sequencing Center, Baylor College of Medicine, United States of America

  8. Wenyi Wang
    Investigator

    Department of Bioinformatics and Computational Biology - Unit 1410, The University of Texas MD Anderson Cancer Center, United States of America

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Summary
AccessionBT007022
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC, C++
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByWenyi Wang