msqrob2
Robust statistical inference for quantitative LC-MS proteomics
Bioconductor version: 3.23 · Package version: 1.20.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
msqrob2 provides a robust linear mixed model framework for assessing differential abundance in MS-based Quantitative proteomics experiments. Our workflows can start from raw peptide intensities or summarised protein expression values. The model parameter estimates can be stabilized by ridge regression, empirical Bayes variance estimation and robust M-estimation. msqrob2's hurde workflow can handle missing data without having to rely on hard-to-verify imputation assumptions, and, outcompetes state-of-the-art methods with and without imputation for both high and low missingness. It builds on QFeature infrastructure for quantitative mass spectrometry data to store the model results together with the raw data and preprocessed data.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("msqrob2")Details
| Maintainer | Lieven Clement <lieven.clement@ugent.be> |
| Author | Lieven Clement [aut, cre] (ORCID: <https://orcid.org/0000-0002-9050-4370>), Laurent Gatto [aut] (ORCID: <https://orcid.org/0000-0002-1520-2268>), Oliver M. Crook [aut] (ORCID: <https://orcid.org/0000-0001-5669-8506>), Adriaan Sticker [ctb], Ludger Goeminne [ctb], Milan Malfait [ctb] (ORCID: <https://orcid.org/0000-0001-9144-3701>), Stijn Vandenbulcke [aut] |
| License | Artistic-2.0 |
| URL | https://github.com/statOmics/msqrob2 |
| Bug Reports | https://github.com/statOmics/msqrob2/issues |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | DifferentialExpression, ExperimentalDesign, ImmunoOncology, MassSpectrometry, Metabolomics, MultipleComparison, Normalization, Preprocessing, Proteomics, Regression, Software, TimeCourse |
| Package Short Url | https://bioconductor.org/packages/msqrob2/ |
Citation
From within R, enter citation("msqrob2"):
Lieven Clement, Laurent Gatto, Oliver M. Crook, Stijn Vandenbulcke. msqrob2: Robust statistical inference for quantitative LC-MS proteomics. doi:10.18129/B9.bioc.msqrob2, R package version 1.20.0, https://bioconductor.org/packages/msqrob2.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
- Introduction to proteomics data analysis - MaxQuant Data Dependent Acquisition spike-in study
- Differential abundance analysis for Data Independent Acquistion (DIA-NN - starting from Precursor.Quantity)
- Differential abundance analysis for Data Independent Acquistion (Spectronaut - starting from FG_MS2RawQuantity)
Download
Follow the installation instructions to use this package in your R session.
| Source package | msqrob2_1.20.0.tar.gz |
| Windows binary (x86_64) | msqrob2_1.20.0.zip |
| macOS binary (arm64) | msqrob2_1.20.0.tgz |
| macOS binary (x86_64) | msqrob2_1.20.0.tgz |
Dependencies
Depends: R (>= 4.1), QFeatures (>= 1.1.2)
Imports: stats, methods, lme4, purrr, BiocParallel, Matrix, MASS, limma, SummarizedExperiment, MultiAssayExperiment, codetools, matrixStats, ggplot2, assertthat, dplyr, grDevices, utils, rlang
Suggests: stringr, ExploreModelMatrix, kableExtra, ComplexHeatmap, scater, multcomp, gridExtra, knitr, BiocStyle, RefManageR, sessioninfo, rmarkdown, testthat, tidyverse, tidyr, plotly, MsDataHub, MSnbase, MsCoreUtils, covr, arrow, data.table, ggcorrplot, iq