Journal
GENOME BIOLOGY
Volume 11, Issue 5, Pages -Publisher
BMC
DOI: 10.1186/gb-2010-11-5-r50
Keywords
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Funding
- NIH [R01 HG004634, R01 HG003903]
- NSF [DMS-0821823]
- NATIONAL HUMAN GENOME RESEARCH INSTITUTE [R01HG003903, R01HG004634] Funding Source: NIH RePORTER
- Direct For Mathematical & Physical Scien [0821823] Funding Source: National Science Foundation
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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 data.
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