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Genetics. 2010 Jun;185(2):405-16. doi: 10.1534/genetics.110.114983. Epub 2010 May 3.

Statistical design and analysis of RNA sequencing data.

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  • 1Department of Statistics, Purdue University, West Lafayette, Indiana 47907, USA.

Abstract

Next-generation sequencing technologies are quickly becoming the preferred approach for characterizing and quantifying entire genomes. Even though data produced from these technologies are proving to be the most informative of any thus far, very little attention has been paid to fundamental design aspects of data collection and analysis, namely sampling, randomization, replication, and blocking. We discuss these concepts in an RNA sequencing framework. Using simulations we demonstrate the benefits of collecting replicated RNA sequencing data according to well known statistical designs that partition the sources of biological and technical variation. Examples of these designs and their corresponding models are presented with the goal of testing differential expression.

PMID:
20439781
[PubMed - indexed for MEDLINE]
PMCID:
PMC2881125
Free PMC Article
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