Package: IsoBayes
Type: Package
Title: IsoBayes: Single Isoform protein inference Method via Bayesian
        Analyses
Version: 1.9.0
Description: 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@R: c(person(given = "Jordy",
  family = "Bollon",
  role = c("aut"),
  email = "jordy.bollon@iit.it"),
  person(given = "Simone",
  family = "Tiberi",
  role = c("aut", "cre"),
  email = "simone.tiberi@unibo.it",
  comment = c(ORCID = "0000-0002-3054-9964")))
biocViews: StatisticalMethod, Bayesian, Proteomics, MassSpectrometry,
        AlternativeSplicing, Sequencing, RNASeq, GeneExpression,
        Genetics, Visualization, Software
License: GPL-3
Depends: R (>= 4.3.0)
Imports: methods, Rcpp, data.table, glue, stats, doParallel, parallel,
        doRNG, foreach, iterators, ggplot2, HDInterval,
        SummarizedExperiment, S4Vectors
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat, BiocStyle
SystemRequirements: C++17
VignetteBuilder: knitr
RoxygenNote: 7.3.2
ByteCompile: true
URL: https://github.com/SimoneTiberi/IsoBayes
BugReports: https://github.com/SimoneTiberi/IsoBayes/issues
Config/pak/sysreqs: zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 15:26:35 UTC
RemoteUrl: https://github.com/bioc/IsoBayes
RemoteRef: HEAD
RemoteSha: 2a6c228b810ae6f813f855a0bd4fb4db3bf7ecdc
NeedsCompilation: yes
Packaged: 2026-01-26 08:55:45 UTC; root
Author: Jordy Bollon [aut],
  Simone Tiberi [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-3054-9964>)
Maintainer: Simone Tiberi <simone.tiberi@unibo.it>
Built: R 4.6.0; aarch64-apple-darwin23; 2026-01-26 08:59:42 UTC; unix
