A scalable, flexible workflow for MethylCap-seq data analysis

Benjamin Rodriguez, Hok Hei Tam, David Frankhouser, Michael Trimarchi, Mark Murphy, Chris Kuo, Deval Parikh, Bryan Ball, Sebastian Schwind, John Curfman, William Blum, Guido Marcucci, Pearlly Yan, Ralf Bundschuh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Advances in whole genome profiling have revolutionized the cancer research field, but at the same time have raised new bioinformatics challenges. For next generation sequencing (NGS), these include data storage, computational costs, sequence processing and alignment, delineating appropriate statistical measures, and data visualization. The NGS application MethylCap-seq involves the in vitro capture of methylated DNA and subsequent analysis of enriched fragments by massively parallel sequencing. Here, we present a scalable, flexible workflow for MethylCap-seq Quality Control, secondary data analysis, tertiary analysis of multiple experimental groups, and data visualization. This workflow and its suite of features will assist biologists in conducting methylation profiling projects and facilitate meaningful biological interpretation.

Original languageEnglish
Title of host publicationProceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
PublisherIEEE Computer Society
Pages1-4
Number of pages4
ISBN (Print)9781467304900
DOIs
StatePublished - Dec 1 2011
Event2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11 - San Antonio, TX, United States
Duration: Dec 4 2011Dec 6 2011

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
Country/TerritoryUnited States
CitySan Antonio, TX
Period12/4/1112/6/11

Keywords

  • Cancer
  • DNA methylation
  • Data analysis
  • Data visualization
  • Epigenetics
  • Next generation sequencing

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