Package: ppcseq
Title: Probabilistic Outlier Identification for RNA Sequencing
        Generalized Linear Models
Version: 1.21.0
Authors@R: 
    person(given = "Stefano",
           family = "Mangiola",
           role = c("aut", "cre"),
           email = "mangiolastefano@gmail.com",
           comment = c(ORCID = "0000-0001-7474-836X"))
Description: Relative transcript abundance has proven to be a valuable
        tool for understanding the function of genes in biological
        systems. For the differential analysis of transcript abundance
        using RNA sequencing data, the negative binomial model is by
        far the most frequently adopted. However, common methods that
        are based on a negative binomial model are not robust to
        extreme outliers, which we found to be abundant in public
        datasets. So far, no rigorous and probabilistic methods for
        detection of outliers have been developed for RNA sequencing
        data, leaving the identification mostly to visual inspection.
        Recent advances in Bayesian computation allow large-scale
        comparison of observed data against its theoretical
        distribution given in a statistical model. Here we propose
        ppcseq, a key quality-control tool for identifying transcripts
        that include outlier data points in differential expression
        analysis, which do not follow a negative binomial distribution.
        Applying ppcseq to analyse several publicly available datasets
        using popular tools, we show that from 3 to 10 percent of
        differentially abundant transcripts across algorithms and
        datasets had statistics inflated by the presence of outliers.
License: GPL-3
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 4.1.0), rstan (>= 2.18.1)
Imports: benchmarkme, dplyr, edgeR, foreach, ggplot2, graphics,
        lifecycle, magrittr, methods, parallel, purrr, Rcpp (>=
        0.12.0), RcppParallel (>= 5.0.1), rlang, rstantools (>= 2.1.1),
        stats, tibble, tidybayes, tidyr (>= 0.8.3.9000), utils
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0),
        RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>=
        2.18.0)
Suggests: knitr, testthat, BiocStyle, rmarkdown
VignetteBuilder: knitr
RdMacros: lifecycle
biocViews: RNASeq, DifferentialExpression, GeneExpression,
        Normalization, Clustering, QualityControl, Sequencing,
        Transcription, Transcriptomics
SystemRequirements: GNU make
RoxygenNote: 7.2.3
Roxygen: list(markdown = TRUE)
URL: https://github.com/stemangiola/ppcseq
BugReports: https://github.com/stemangiola/ppcseq/issues
Config/testthat/edition: 3
Config/pak/sysreqs: make libicu-dev libssl-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:55:44 UTC
RemoteUrl: https://github.com/bioc/ppcseq
RemoteRef: HEAD
RemoteSha: cac1c6d9796e15d870cab0e5e1b3d83f3d95a7a4
NeedsCompilation: yes
Packaged: 2026-05-30 09:43:49 UTC; root
Author: Stefano Mangiola [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-7474-836X>)
Maintainer: Stefano Mangiola <mangiolastefano@gmail.com>
Built: R 4.6.0; x86_64-w64-mingw32; 2026-05-30 10:15:08 UTC; windows
Archs: x64
