Chapter title |
edgeR for Differential RNA-seq and ChIP-seq Analysis: An Application to Stem Cell Biology.
|
---|---|
Chapter number | 3 |
Book title |
Stem Cell Transcriptional Networks
|
Published in |
Methods in molecular biology, January 2014
|
DOI | 10.1007/978-1-4939-0512-6_3 |
Pubmed ID | |
Book ISBNs |
978-1-4939-0511-9, 978-1-4939-0512-6
|
Authors |
Olga Nikolayeva, Mark D Robinson, Mark D. Robinson, Nikolayeva, Olga, Robinson, Mark D. |
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. |
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Mendeley readers
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Unknown | 92 | 98% |
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Researcher | 21 | 22% |
Student > Master | 7 | 7% |
Student > Doctoral Student | 6 | 6% |
Professor | 5 | 5% |
Other | 15 | 16% |
Unknown | 12 | 13% |
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Medicine and Dentistry | 9 | 10% |
Computer Science | 6 | 6% |
Immunology and Microbiology | 3 | 3% |
Other | 0 | 0% |
Unknown | 13 | 14% |