Model-based and context-specific background correction and differential methylation testing for MBDCap-seq

Yuanhang Liu, Desiree Wilson, Robin J. Leach, Yidong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

DNA methylation in promoter regions has long been considered an essential mechanism of transcriptional regulation, and it has been demonstrated to be involved in cell development, tumor progression and aging. Methyl-CpG binding domain-based capture followed by high throughput sequencing (MBDCap-seq) is widely used to examine DNA methylation pattern genome-wide. Current MBDCap-seq data analysis approaches focus on measurement of methylated CpG sequence reads, without considering genomic characteristics and tissue-specific context and their impact to the amount of methylated DNA measurement (signal) and background fluctuation (noise). Therefore, specific software needs to be developed to process MBDCap-seq datasets. Here we presented a novel algorithm, termed MBDDiff, implemented as an R package that is designed specifically for processing MBDCap-seq datasets. MBDDiff contains three modules: quality assessment of datasets and quantification of DNA methylation; determination of differential methylation of promoter regions; and visualization functionalities. Simulation studies were carried out to demonstrate the accuracy of MBDDiff algorithm in detecting differential methylation in promoter regions. We also tested functionalities of MBDDiff to a set of in-house prostate cancer samples and a set of public-domain triple negative breast cancer samples profiled with MBDCap-seq protocol, and demonstrated the capability of identifying differential methylation of promoter regions of genes that might contribute to cancer development and progression.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Editorslng. Matthieu Schapranow, Jiayu Zhou, Xiaohua Tony Hu, Bin Ma, Sanguthevar Rajasekaran, Satoru Miyano, Illhoi Yoo, Brian Pierce, Amarda Shehu, Vijay K. Gombar, Brian Chen, Vinay Pai, Jun Huan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages214-219
Number of pages6
ISBN (Electronic)9781467367981
DOIs
StatePublished - Dec 16 2015
EventIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States
Duration: Nov 9 2015Nov 12 2015

Publication series

NameProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015

Other

OtherIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
Country/TerritoryUnited States
CityWashington
Period11/9/1511/12/15

Keywords

  • DNA Methylation
  • Differential methylated regions
  • Differentially methylation
  • MBDCap-seq
  • MBDDiff
  • XBSeq

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Health Informatics
  • Biomedical Engineering

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