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Methods Mol Biol. 2014;1150:45-79. doi: 10.1007/978-1-4939-0512-6_3.

edgeR for differential RNA-seq and ChIP-seq analysis: an application to stem cell biology.

Author information

1
Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland.

Abstract

The edgeR package, an R-based tool within the Bioconductor project, offers a flexible statistical framework for detection of changes in abundance based on counts. In this chapter, we illustrate the use of edgeR on a human embryonic stem cell dataset, in particular for RNA-seq and ChIP-seq data. We focus on a step-by-step statistical analysis of differential expression, going from raw data to a list of putative differentially expressed genes and give examples of integrative analysis using the ChIP-seq data. We emphasize data quality spot checks and the use of positive controls throughout the process and give practical recommendations for reproducible research.

PMID:
24743990
DOI:
10.1007/978-1-4939-0512-6_3
[Indexed for MEDLINE]

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