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Modeling non-uniformity in short-read rates in RNA-Seq data.
Genome Biol. 2010 May 11;11(5):R50
Authors: Li J, Jiang H, Wong WH
ABSTRACT: After mapping, RNA-Seq data can be summarized by a sequence of read counts commonly modeled as Poisson variables with constant rates along each transcript, which actually fit data poorly. We suggest using variable rates for different positions, and propose two models to predict these rates based on local sequences. These models explain more than 50% of the variations and can lead to improved estimates of gene and isoform expressions for both Illumina and Applied Biosystems (ABI) data.
PMID: 20459815 [PubMed - as supplied by publisher]
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Modeling non-uniformity in short-read rates in RNA-Seq data.
Genome Biol. 2010 May 11;11(5):R50
Authors: Li J, Jiang H, Wong WH
ABSTRACT: After mapping, RNA-Seq data can be summarized by a sequence of read counts commonly modeled as Poisson variables with constant rates along each transcript, which actually fit data poorly. We suggest using variable rates for different positions, and propose two models to predict these rates based on local sequences. These models explain more than 50% of the variations and can lead to improved estimates of gene and isoform expressions for both Illumina and Applied Biosystems (ABI) data.
PMID: 20459815 [PubMed - as supplied by publisher]
More...
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