Modeling non-uniformity in short-read rates in RNA-Seq data

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...

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Detalles Bibliográficos
Autores principales: Li, Jun, Jiang, Hui, Wong, Wing Hung
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898062/
https://www.ncbi.nlm.nih.gov/pubmed/20459815
http://dx.doi.org/10.1186/gb-2010-11-5-r50
Descripción
Sumario: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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