Format

Send to

Choose Destination
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.

Author information

1
Department 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
PMCID:
PMC2881125
DOI:
10.1534/genetics.110.114983
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for HighWire Icon for PubMed Central
Loading ...
Support Center