DaparToolshed
Tools for the Differential Analysis of Proteins Abundance with R
Bioconductor version: 3.24 · Package version: 0.99.38
The package DaparToolshed is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. It is an update of our previous package DAPAR and contains more functions to analyze the data and uses MultAssayExperiment and SummarizedExperiment data structures. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("DaparToolshed") Details
| Maintainer | Samuel Wieczorek <samuel.wieczorek@cea.fr> |
| Author | Samuel Wieczorek [cre, aut] (ORCID: <https://orcid.org/0000-0002-5016-1203>), Thomas Burger [aut], Enora Fremy [ctb], Manon Gaudin [ctb] |
| License | Artistic-2.0 |
| URL | https://github.com/edyp-lab/DaparToolshed, https://edyp-lab.github.io/DaparToolshed/ |
| Bug Reports | https://github.com/edyp-lab/DaparToolshed/issues |
| Downloads rank | 56 |
| Source branch | devel |
| biocViews | DataImport, MassSpectrometry, Normalization, Preprocessing, Proteomics, QualityControl, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | DaparToolshed_0.99.38.tar.gz |
| Windows binary (x86_64) | DaparToolshed_0.99.38.zip |
| macOS binary (arm64) | DaparToolshed_0.99.38.tgz |
| macOS binary (x86_64) | DaparToolshed_0.99.38.tgz |
Dependencies
Depends: R (>= 4.5.0)
Imports: BiocGenerics, matrixStats, S4Vectors, SummarizedExperiment, openxlsx, QFeatures (>= 1.16), methods, MsCoreUtils, AnnotationFilter, RColorBrewer, plotly, stats, utils, tibble, Matrix, stringr, graph, igraph, preprocessCore, dplyr
Suggests: BiocManager, visNetwork, htmlwidgets, rhandsontable, shinyalert, shinyjs, sos, knitr, shinyBS, MultiAssayExperiment, PSMatch, lme4, DT, shinyWidgets, vsn, cp4p, limma, imp4p (>= 0.9), impute, apcluster, diptest, cluster, rmarkdown, BiocStyle, testthat, FactoMineR, factoextra, colourpicker, readxl, grDevices, forcats, multcomp, purrr, gplots, tidyr, Pirat, shinyjqui