_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
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r-bandits 1.24.0
Propagated dependencies: r-biocparallel@1.42.0 r-data-table@1.17.2 r-doparallel@1.0.17 r-dorng@1.8.6.2 r-drimseq@1.36.0 r-foreach@1.5.2 r-ggplot2@3.5.2 r-mass@7.3-65 r-r-utils@2.13.0 r-rcpp@1.0.14 r-rcpparmadillo@14.4.2-1
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://github.com/SimoneTiberi/BANDITS
Licenses: GPL 3+
Synopsis: Bayesian analysis of differential splicing
Description:

BANDITS is a Bayesian hierarchical model for detecting differential splicing of genes and transcripts, via DTU (differential transcript usage), between two or more conditions. The method uses a Bayesian hierarchical framework, which allows for sample specific proportions in a Dirichlet-Multinomial model, and samples the allocation of fragments to the transcripts. Parameters are inferred via MCMC (Markov chain Monte Carlo) techniques and a DTU test is performed via a multivariate Wald test on the posterior densities for the average relative abundance of transcripts.

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