Statistical Modeling of RNA-Seq Data

Details Statistical Modeling of RNA-Seq Data Statistical Modeling of RNA-Seq Data

2011-06-16

arxiv.org/abs/1106.3211v1

Statistical Science 2011, Vol. 26, No. 1, 62-83

Statistics

Methodology

Published in at http://dx.doi.org/10.1214/10-STS343 the Statistical Science (http://www.imstat.org/sts/) by the Institute of M

Scientific paper

10.1214/10-STS343

Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest. This paper introduces a statistical model for estimating isoform abundance from RNA-Seq data and is flexible enough to accommodate both single end and paired end RNA-Seq data and sampling bias along the length of the transcript. Based on the derivation of minimal sufficient statistics for the model, a computationally feasible implementation of the maximum likelihood estimator of the model is provided. Further, it is shown that using paired end RNA-Seq provides more accurate isoform abundance estimates than single end sequencing at fixed sequencing depth. Simulation studies are also given.

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