Publication: BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty
BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty
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Tiberi, S., & Robinson, M. D. (2020). BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty. Genome Biology, 21, 69. https://doi.org/10.1186/s13059-020-01967-8
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Alternative splicing is a biological process during gene expression that allows a single gene to code for multiple proteins. However, splicing patterns can be altered in some conditions or diseases. Here, we present BANDITS, a R/Bioconductor package to perform differential splicing, at both gene and transcript level, based on RNA-seq data. BANDITS uses a Bayesian hierarchical structure to explicitly model the variability between samples and treats the transcript allocation of reads as latent variables. We perform an extensive benchmar
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Tiberi, S., & Robinson, M. D. (2020). BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty. Genome Biology, 21, 69. https://doi.org/10.1186/s13059-020-01967-8