limpca
An R package for the linear modeling of high-dimensional designed data based on ASCA/APCA family of methods
Bioconductor version: 3.23 · Package version: 1.8.0
This package has for objectives to provide a method to make Linear Models for high-dimensional designed data. limpca applies a GLM (General Linear Model) version of ASCA and APCA to analyse multivariate sample profiles generated by an experimental design. ASCA/APCA provide powerful visualization tools for multivariate structures in the space of each effect of the statistical model linked to the experimental design and contrarily to MANOVA, it can deal with mutlivariate datasets having more variables than observations. This method can handle unbalanced design.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("limpca") Details
| Maintainer | Manon Martin <manon.martin@uclouvain.be> |
| Author | Bernadette Govaerts [aut, ths], Sebastien Franceschini [ctb], Robin van Oirbeek [ctb], Michel Thiel [aut], Pascal de Tullio [dtc], Manon Martin [aut, cre] (ORCID: <https://orcid.org/0000-0003-4800-0942>), Nadia Benaiche [ctb] |
| License | Artistic-2.0 |
| URL | https://github.com/ManonMartin/limpca, https://manonmartin.github.io/limpca/ |
| Bug Reports | https://github.com/ManonMartin/limpca/issues |
| Downloads rank | 182 |
| Source branch | RELEASE_3_23 |
| biocViews | ExperimentalDesign, GeneExpression, Metabolomics, MultipleComparison, PrincipalComponent, Regression, Software, StatisticalMethod, Visualization |
Documentation
- Application of limpca on the Trout transcriptomic dataset.
- Application of limpca on the UCH metabolomics dataset.
- Get started with limpca.
Download
Dependencies
Depends: R (>= 3.5.0)
Imports: ggplot2, stringr, plyr, ggrepel, reshape2, grDevices, graphics, doParallel, parallel, dplyr, tibble, tidyr, ggsci, tidyverse, methods, stats, SummarizedExperiment, S4Vectors
Suggests: BiocStyle, pander, rmarkdown, car, gridExtra, knitr, testthat (>= 3.0.0)