Introduction

In this article, we introduce a robust and efficient strategy for deriving global and allele-specific copy number alternations (CNA) from cancer whole exome sequencing data based on Log R ratios and B-allele frequencies. Applying the approach to the analysis of over 200 skin cancer samples, we demonstrate its utility for discovering distinct CNA events and for deriving ancillary information such as tumor purity.https://github.com/xfwang/CLOSE CONTACT: xuefeng.wang@stonybrook.edu or michael.krauthammer@yale.eduSupplementary data are available at Bioinformatics online.

Publications

  1. Global copy number profiling of cancer genomes.
    Cite this
    Wang X, Chen M, Yu X, Pornputtapong N, Chen H, Zhang NR, Powers RS, Krauthammer M, 2016-03-01 - Bioinformatics (Oxford, England)

Credits

  1. Xuefeng Wang
    Developer

    Department of Family, Population & Preventive Medicine, United States of America

  2. Mengjie Chen
    Developer

    Departments of Biostatistics and Genetics, University of North Carolina, United States of America

  3. Xiaoqing Yu
    Developer

  4. Natapol Pornputtapong
    Developer

    Program in Computational Biology and Bioinformatics, Yale University, United States of America

  5. Hao Chen
    Developer

    Department of Statistics, University of California, United States of America

  6. Nancy R Zhang
    Developer

    Department of Statistics, The Wharton School

  7. R Scott Powers
    Developer

    Department of Pathology, Stony Brook University, United States of America

  8. Michael Krauthammer
    Investigator

    Program in Computational Biology and Bioinformatics, Yale University, United States of America

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Summary
AccessionBT006971
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByMichael Krauthammer