Introduction

We present CANOES, an algorithm for the detection of rare copy number variants from exome sequencing data. CANOES models read counts using a negative binomial distribution and estimates variance of the read counts using a regression-based approach based on selected reference samples in a given dataset. We test CANOES on a family-based exome sequencing dataset, and show that its sensitivity and specificity is comparable to that of XHMM. Moreover, the method is complementary to Gaussian approximation-based methods (e.g. XHMM or CoNIFER). When CANOES is used in combination with these methods, it will be possible to produce high accuracy calls, as demonstrated by a much reduced and more realistic de novo rate in results from trio data.

Publications

  1. CANOES: detecting rare copy number variants from whole exome sequencing data.
    Cite this
    Backenroth D, Homsy J, Murillo LR, Glessner J, Lin E, Brueckner M, Lifton R, Goldmuntz E, Chung WK, Shen Y, 2014-07-01 - Nucleic acids research

Credits

  1. Daniel Backenroth
    Developer

    Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, United States of America

  2. Jason Homsy
    Developer

    Cardiovascular Research Center, Massachusetts General Hospital, United States of America

  3. Laura R Murillo
    Developer

    Departments of Pediatrics and Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, United States of America

  4. Joe Glessner
    Developer

    Center for Applied Genomics, Children's Hospital of Philadelphia, United States of America

  5. Edwin Lin
    Developer

    Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, United States of America

  6. Martina Brueckner
    Developer

    Department of Genetics, Yale University School of Medicine, United States of America

  7. Richard Lifton
    Developer

    Department of Genetics, Yale University School of Medicine, United States of America

  8. Elizabeth Goldmuntz
    Developer

    Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, United States of America

  9. Wendy K Chung
    Developer

    Departments of Pediatrics and Medicine, Columbia University Medical Center

  10. Yufeng Shen
    Investigator

    Departments of Systems Biology and Biomedical Informatics, Columbia University Medical Center, United States of America

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Summary
AccessionBT002113
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByYufeng Shen