Package: RNAdecay
Date: 2023-10-25
Title: Maximum Likelihood Decay Modeling of RNA Degradation Data
Version: 1.30.0
Authors@R: c(person("Reed", "Sorenson", email = "reedssorenson@gmail.com", role = c("aut", "cre"),comment=c(ORCID="0000-0001-8650-0601")), person("Katrina", "Johnson", email = "kjohnson@math.utah.edu", role = c("aut")),person("Frederick", "Adler", email = "adler@math.utah.edu", role = c("aut")),person("Leslie", "Sieburth", email = "sieburth@biology.utah.edu", role = c("aut"),comment=c(ORCID="0000-0001-6691-2000")))
Description: RNA degradation is monitored through measurement of RNA
        abundance after inhibiting RNA synthesis. This package has
        functions and example scripts to facilitate (1) data
        normalization, (2) data modeling using constant decay rate or
        time-dependent decay rate models, (3) the evaluation of
        treatment or genotype effects, and (4) plotting of the data and
        models. Data Normalization: functions and scripts make easy the
        normalization to the initial (T0) RNA abundance, as well as a
        method to correct for artificial inflation of Reads per Million
        (RPM) abundance in global assessments as the total size of the
        RNA pool decreases. Modeling: Normalized data is then modeled
        using maximum likelihood to fit parameters. For making
        treatment or genotype comparisons (up to four), the modeling
        step models all possible treatment effects on each gene by
        repeating the modeling with constraints on the model parameters
        (i.e., the decay rate of treatments A and B are modeled once
        with them being equal and again allowing them to both vary
        independently). Model Selection: The AICc value is calculated
        for each model, and the model with the lowest AICc is chosen.
        Modeling results of selected models are then compiled into a
        single data frame. Graphical Plotting: functions are provided
        to easily visualize decay data model, or half-life
        distributions using ggplot2 package functions.
Depends: R (>= 4.3)
Imports: stats, grDevices, grid, ggplot2, gplots, utils, TMB, nloptr,
        scales
Suggests: parallel, knitr, reshape2, rmarkdown
biocViews: ImmunoOncology, Software, GeneExpression, GeneRegulation,
        DifferentialExpression, Transcription, Transcriptomics,
        TimeCourse, Regression, RNASeq, Normalization, WorkflowStep
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
VignetteBuilder: knitr
Config/pak/sysreqs: cmake
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 15:27:20 UTC
RemoteUrl: https://github.com/bioc/RNAdecay
RemoteRef: RELEASE_3_22
RemoteSha: 49e3210734b85d6db0a08e3213b963234f2cedfe
NeedsCompilation: yes
Packaged: 2025-11-16 10:08:38 UTC; root
Author: Reed Sorenson [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-8650-0601>),
  Katrina Johnson [aut],
  Frederick Adler [aut],
  Leslie Sieburth [aut] (ORCID: <https://orcid.org/0000-0001-6691-2000>)
Maintainer: Reed Sorenson <reedssorenson@gmail.com>
Built: R 4.5.2; x86_64-w64-mingw32; 2025-11-16 10:13:19 UTC; windows
Archs: x64
