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README.md
limpca ================ <!-- badges: start --> [![R-CMD-check](https://github.com/ManonMartin/limpca/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/ManonMartin/limpca/actions/workflows/check-standard.yaml) <!-- badges: end --> The web page of the package can be accessed here: <https://manonmartin.github.io/limpca/> `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. `limpca` presents different advantages compared to other software in this field: (1) it is able to treat any balanced or unbalanced experimental design for fixed categorical factors, (2) it offers optimized methods to calculate effect importance and test their significance, (3) it allows the user to represent data and ASCA/APCA results with various and rich ggplot2-based graphical outputs that are highly customizable and (4) the package is open to future extensions to more sophisticated statistical models. ## Installation Installation from Bioconductor: ```r if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("limpca") ``` ## Additional information For any enquiry, you can open an [issue](https://github.com/ManonMartin/limpca/issues) on Github or send an email to the package authors: <bernadette.govaerts@uclouvain.be> ; <michel.thiel@uclouvain.be> or <manon.martin@uclouvain.be>.