Introduction

Spontaneous (de novo) mutations play an important role in the disease etiology of a range of complex diseases. Identifying de novo mutations (DNMs) in sporadic cases provides an effective strategy to find genes or genomic regions implicated in the genetics of disease. High-throughput next-generation sequencing enables genome- or exome-wide detection of DNMs by sequencing parents-proband trios. It is challenging to sift true mutations through massive amount of noise due to sequencing error and alignment artifacts. One of the critical limitations of existing methods is that for all genomic regions the same pre-specified mutation rate is assumed, which has a significant impact on the DNM calling accuracy.In this study, we developed and implemented a novel Bayesian framework for DNM calling in trios (TrioDeNovo), which overcomes these limitations by disentangling prior mutation rates from evaluation of the likelihood of the data so that flexible priors can be adjusted post-hoc at different genomic sites. Through extensively simulations and application to real data we showed that this new method has improved sensitivity and specificity over existing methods, and provides a flexible framework to further improve the efficiency by incorporating proper priors. The accuracy is further improved using effective filtering based on sequence alignment characteristics.The C++ source code implementing TrioDeNovo is freely available at https://medschool.vanderbilt.edu/cgg.bingshan.li@vanderbilt.eduSupplementary data are available at Bioinformatics online.

Publications

  1. A Bayesian framework for de novo mutation calling in parents-offspring trios.
    Cite this
    Wei Q, Zhan X, Zhong X, Liu Y, Han Y, Chen W, Li B, 2015-05-01 - Bioinformatics (Oxford, England)

Credits

  1. Qiang Wei
    Developer

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

  2. Xiaowei Zhan
    Developer

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

  3. Xue Zhong
    Developer

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

  4. Yongzhuang Liu
    Developer

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

  5. Yujun Han
    Developer

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

  6. Wei Chen
    Developer

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

  7. Bingshan Li
    Investigator

    Department of Molecular Physiology and Biophysics, Vanderbilt University, United States of America

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Summary
AccessionBT000904
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByBingshan Li