Introduction

DNA methylation is an epigenetic modification critical for normal development and diseases. The determination of genome-wide DNA methylation at single-nucleotide resolution is made possible by sequencing bisulfite treated DNA with next generation high-throughput sequencing. However, aligning bisulfite short reads to a reference genome remains challenging as only a limited proportion of them (around 50-70%) can be aligned uniquely; a significant proportion, known as multireads, are mapped to multiple locations and thus discarded from downstream analyses, causing financial waste and biased methylation inference. To address this issue, we develop a Bayesian model that assigns multireads to their most likely locations based on the posterior probability derived from information hidden in uniquely aligned reads. Analyses of both simulated data and real hairpin bisulfite sequencing data show that our method can effectively assign approximately 70% of the multireads to their best locations with up to 90% accuracy, leading to a significant increase in the overall mapping efficiency. Moreover, the assignment model shows robust performance with low coverage depth, making it particularly attractive considering the prohibitive cost of bisulfite sequencing. Additionally, results show that longer reads help improve the performance of the assignment model. The assignment model is also robust to varying degrees of methylation and varying sequencing error rates. Finally, incorporating prior knowledge on mutation rate and context specific methylation level into the assignment model increases inference accuracy. The assignment model is implemented in the BAM-ABS package and freely available at https://github.com/zhanglabvt/BAM_ABS.

Publications

  1. A Bayesian Assignment Method for Ambiguous Bisulfite Short Reads.
    Cite this
    Tran H, Wu X, Tithi S, Sun MA, Xie H, Zhang L, 2016-01-01 - PLoS ONE

Credits

  1. Hong Tran
    Developer

    Department of Computer Science, Virginia Polytechnic Institute and State University (Virginia Tech), United States of America

  2. Xiaowei Wu
    Developer

    Department of Statistics, Virginia Polytechnic Institute and State University (Virginia Tech), United States of America

  3. Saima Tithi
    Developer

    Department of Computer Science, Virginia Polytechnic Institute and State University (Virginia Tech), United States of America

  4. Ming-An Sun
    Developer

    Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University (Virginia Tech), United States of America

  5. Hehuang Xie
    Developer

    Department of Biological Sciences, Virginia Polytechnic Institute and State University(Virginia Tech), United States of America

  6. Liqing Zhang
    Investigator

    Department of Computer Science, Virginia Polytechnic Institute and State University (Virginia Tech), United States of America

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Summary
AccessionBT007016
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByLiqing Zhang