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• W3105872783 abstract "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." @default.
• W3105872783 created "2020-11-23" @default.
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• W3105872783 date "2011-02-01" @default.
• W3105872783 modified "2023-09-30" @default.
• W3105872783 title "Statistical Modeling of RNA-Seq Data" @default.
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• W3105872783 doi "https://doi.org/10.1214/10-sts343" @default.
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• W3105872783 hasPublicationYear "2011" @default.
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