msqrob2
Robust statistical inference for quantitative LC-MS proteomics
Bioconductor version: 3.23 · Package version: 1.20.0
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 |
| Downloads rank | 414 |
| Source branch | RELEASE_3_23 |
| biocViews | DifferentialExpression, ExperimentalDesign, ImmunoOncology, MassSpectrometry, Metabolomics, MultipleComparison, Normalization, Preprocessing, Proteomics, Regression, Software, TimeCourse |
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)
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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