title: A Scalable, Flexible Workflow for MethylCap-Seq Data Analysis.
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.
authors.affiliation: The Ohio State University Comprehensive Cancer Center Columbus, Ohio, USA.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Rodriguez
authors.forename: Hok-Hei
authors.initials: HH
authors.lastname: Tam
authors.forename: David
authors.initials: D
authors.lastname: Frankhouser
authors.forename: Michael
authors.initials: M
authors.lastname: Trimarchi
authors.forename: Mark
authors.initials: M
authors.lastname: Murphy
authors.forename: Chris
authors.initials: C
authors.lastname: Kuo
authors.forename: Deval
authors.initials: D
authors.lastname: Parikh
authors.forename: Bryan
authors.initials: B
authors.lastname: Ball
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schwind
authors.forename: John
authors.initials: J
authors.lastname: Curfman
authors.forename: William
authors.initials: W
authors.lastname: Blum
authors.forename: Guido
authors.initials: G
authors.lastname: Marcucci
authors.forename: Pearlly
authors.initials: P
authors.lastname: Yan
authors.forename: Ralf
authors.initials: R
authors.lastname: Bundschuh