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cff-version: 1.2.0
message: 'To cite package "BUMHMM" in publications use:'
type: software
license: GPL-3.0-only
title: 'BUMHMM: Computational pipeline for computing probability of modification from
  structure probing experiment data'
version: 1.29.0
abstract: This is a probabilistic modelling pipeline for computing per- nucleotide
  posterior probabilities of modification from the data collected in structure probing
  experiments. The model supports multiple experimental replicates and empirically
  corrects coverage- and sequence-dependent biases. The model utilises the measure
  of a "drop-off rate" for each nucleotide, which is compared between replicates through
  a log-ratio (LDR). The LDRs between control replicates define a null distribution
  of variability in drop-off rate observed by chance and LDRs between treatment and
  control replicates gets compared to this distribution. Resulting empirical p-values
  (probability of being "drawn" from the null distribution) are used as observations
  in a Hidden Markov Model with a Beta-Uniform Mixture model used as an emission model.
  The resulting posterior probabilities indicate the probability of a nucleotide of
  having being modified in a structure probing experiment.
authors:
- family-names: Selega
  given-names: Alina
  email: alina.selega@gmail.com
- family-names: Granneman
  given-names: Sander
- family-names: Sanguinetti
  given-names: Guido
preferred-citation:
  type: manual
  title: 'BUMHMM: Computational pipeline for computing probability of modification
    from structure probing experiment data.'
  authors:
  - family-names: Selega
    given-names: Alina
    email: alina.selega@gmail.com
  - family-names: Granneman
    given-names: Sander
  - family-names: Sanguinetti
    given-names: Guido
  year: '2016'
  url: http://www.bioconductor.org/packages/BUMHMM
  notes: https://github.com/alinaselega/BUMHMM - R package version 1.29.0
repository: https://bioc.r-universe.dev
date-released: '2021-11-20'
contact:
- family-names: Selega
  given-names: Alina
  email: alina.selega@gmail.com
references:
- type: article
  title: Robust statistical modeling improves sensitivity of high-throughput RNA structure
    probing experiments
  authors:
  - family-names: Selega
    given-names: Alina
  - family-names: Sirocchi
    given-names: Christel
  - family-names: Iosub
    given-names: Ira
  - family-names: Granneman
    given-names: Sander
  - family-names: Sanguinetti
    given-names: Guido
  year: '2016'
  journal: Nature Methods
  doi: 10.1038/nmeth.4068
  url: http://www.nature.com/nmeth/journal/v14/n1/full/nmeth.4068.html