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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "IsoBayes" in publications use:'
type: software
license: GPL-3.0-only
title: 'IsoBayes: IsoBayes: Single Isoform protein inference Method via Bayesian Analyses'
version: 1.3.2
doi: 10.32614/CRAN.package.IsoBayes
abstract: 'IsoBayes is a Bayesian method to perform inference on single protein isoforms.
  Our approach infers the presence/absence of protein isoforms, and also estimates
  their abundance; additionally, it provides a measure of the uncertainty of these
  estimates, via: i) the posterior probability that a protein isoform is present in
  the sample; ii) a posterior credible interval of its abundance. IsoBayes inputs
  liquid cromatography mass spectrometry (MS) data, and can work with both PSM counts,
  and intensities. When available, trascript isoform abundances (i.e., TPMs) are also
  incorporated: TPMs are used to formulate an informative prior for the respective
  protein isoform relative abundance. We further identify isoforms where the relative
  abundance of proteins and transcripts significantly differ. We use a two-layer latent
  variable approach to model two sources of uncertainty typical of MS data: i) peptides
  may be erroneously detected (even when absent); ii) many peptides are compatible
  with multiple protein isoforms. In the first layer, we sample the presence/absence
  of each peptide based on its estimated probability of being mistakenly detected,
  also known as PEP (i.e., posterior error probability). In the second layer, for
  peptides that were estimated as being present, we allocate their abundance across
  the protein isoforms they map to. These two steps allow us to recover the presence
  and abundance of each protein isoform.'
authors:
- family-names: Bollon
  given-names: Jordy
  email: jordy.bollon@iit.it
- family-names: Tiberi
  given-names: Simone
  email: simone.tiberi@unibo.it
  orcid: https://orcid.org/0000-0002-3054-9964
repository: https://bioc.r-universe.dev
repository-code: https://github.com/SimoneTiberi/IsoBayes
commit: 53c46f5384336f80af1d2288cc5183f5acfeddb2
url: https://github.com/SimoneTiberi/IsoBayes
contact:
- family-names: Tiberi
  given-names: Simone
  email: simone.tiberi@unibo.it
  orcid: https://orcid.org/0000-0002-3054-9964