Bioconductor version: Release (3.13)
The QFeatures infrastructure enables the management and processing of quantitative features for high-throughput mass spectrometry assays. It provides a familiar Bioconductor user experience to manages quantitative data across different assay levels (such as peptide spectrum matches, peptides and proteins) in a coherent and tractable format.
Author: Laurent Gatto [aut, cre] , Christophe Vanderaa [aut]
Maintainer: Laurent Gatto <laurent.gatto at uclouvain.be>
Citation (from within R,
enter citation("QFeatures")
):
To install this package, start R (version "4.1") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("QFeatures")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("QFeatures")
HTML | R Script | Processing quantitative proteomics data with QFeatures |
HTML | R Script | Quantitative features for mass spectrometry data |
Reference Manual | ||
Text | NEWS |
biocViews | Infrastructure, MassSpectrometry, Metabolomics, Proteomics, Software |
Version | 1.2.0 |
In Bioconductor since | BioC 3.12 (R-4.0) (1 year) |
License | Artistic-2.0 |
Depends | R (>= 4.0), MultiAssayExperiment |
Imports | methods, stats, utils, S4Vectors, IRanges, SummarizedExperiment, BiocGenerics, ProtGenerics(>= 1.19.3), AnnotationFilter, lazyeval, Biobase, MsCoreUtils(>= 1.1.2) |
LinkingTo | |
Suggests | SingleCellExperiment, HDF5Array, msdata, ggplot2, gplots, dplyr, limma, magrittr, DT, shiny, shinydashboard, testthat, knitr, BiocStyle, rmarkdown, vsn, preprocessCore, matrixStats, imputeLCMD, pcaMethods, impute, norm |
SystemRequirements | |
Enhances | |
URL | https://github.com/RforMassSpectrometry/QFeatures |
BugReports | https://github.com/RforMassSpectrometry/QFeatures/issues |
Depends On Me | msqrob2, scp, scpdata |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | QFeatures_1.2.0.tar.gz |
Windows Binary | QFeatures_1.2.0.zip |
macOS 10.13 (High Sierra) | QFeatures_1.2.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/QFeatures |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/QFeatures |
Package Short Url | https://bioconductor.org/packages/QFeatures/ |
Package Downloads Report | Download Stats |
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