A multivariate and non-parametric batch effect correction framework
based on Projection to Latent Structures Discriminant Analysis for
microbiome data. This repository contains the R
package hosted on
Bioconductor.
(macOS users only: Ensure you have installed XQuartz first.)
Make sure you have the latest R version and the latest BiocManager
package installed following these
instructions.
## install BiocManager if not installed
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
Ensure the following returns TRUE
, or follow the guidelines provided
by the output.
BiocManager::valid()
You can install PLSDAbatch
using the following code:
BiocManager::install('PLSDAbatch')
Install the GitHub version with:
# without vignette
BiocManager::install("EvaYiwenWang/PLSDAbatch")
# with vignette
devtools::install_github("https://github.com/EvaYiwenWang/PLSDAbatch", build_vignettes = T)
library(PLSDAbatch)
## names
ls('package:PLSDAbatch')
## names and details
lsf.str('package:PLSDAbatch')
browseVignettes("PLSDAbatch")
Wang, Y., & Lê Cao, K. A. (2023). PLSDA-batch: a multivariate framework to correct for batch effects in microbiome data. Briefings in Bioinformatics, 24(2), bbac622.
https://academic.oup.com/bib/article/24/2/bbac622/6991121 (The mentioned simulations and analyses in the paper are separately stored here.)
- submitted to Bioconductor.