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A scalable, flexible workflow for MethylCap-seq data analysis.

Authors :
Rodriguez, Benjamin
Tam, Hok-Hei
Frankhouser, David
Trimarchi, Michael
Murphy, Mark
Kuo, Chris
Parikh, Deval
Ball, Bryan
Schwind, Sebastian
Curfman, John
Blum, William
Marcucci, Guido
Yan, Pearlly
Bundschuh, Ralf
Source :
2011 IEEE International Workshop on Genomic Signal Processing & Statistics (GENSIPS); 1/ 1/2011, p1-4, 4p
Publication Year :
2011

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. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISBNs :
9781467304917
Database :
Complementary Index
Journal :
2011 IEEE International Workshop on Genomic Signal Processing & Statistics (GENSIPS)
Publication Type :
Conference
Accession number :
86483634
Full Text :
https://doi.org/10.1109/GENSiPS.2011.6169426