Quantifying alternative splicing from paired-end RNA-sequencing data

DOI10.1214/13-AOAS687zbMath1454.62388arXiv1405.0788WikidataQ30577352 ScholiaQ30577352MaRDI QIDQ2453673

Almond Stöcker, David Rossell, Camille Stephan-Otto Attolini, Manuel Kroiss

Publication date: 10 June 2014

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1405.0788

zbMATH Keywords

estimationBayesian modelingalternative splicingRNA-Seq

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (5)

A Markov random field-based approach for joint estimation of differentially expressed genes in mouse transcriptome data ⋮ MSIQ: joint modeling of multiple RNA-seq samples for accurate isoform quantification ⋮ Bayesian estimation of differential transcript usage from RNA-seq data ⋮ Corrigendum: Quantifying alternative splicing from paired-end RNA-sequencing data ⋮ Quantifying alternative splicing from paired-end RNA-sequencing data

Uses Software

• R
• survival
• Soap
• casper
• TopHat
• SpliceTrap
• BWA

Cites Work

• Unnamed Item
• Unnamed Item
• Statistical modeling of RNA-Seq data
• Quantifying alternative splicing from paired-end RNA-sequencing data
• Nonparametric Estimation from Incomplete Observations

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