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PLSDAbatch

PLSDA-batch

Bioconductor version: 3.23 · Package version: 2.0.0

A novel framework to correct for batch effects prior to any downstream analysis in microbiome data based on Projection to Latent Structures Discriminant Analysis. The main method is named “PLSDA-batch”. It first estimates treatment and batch variation with latent components, then subtracts batch-associated components from the data whilst preserving biological variation of interest. PLSDA-batch is highly suitable for microbiome data as it is non-parametric, multivariate and allows for ordination and data visualisation. Combined with centered log-ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far. Two other variants are proposed for 1/ unbalanced batch x treatment designs that are commonly encountered in studies with small sample sizes, and for 2/ selection of discriminative variables amongst treatment groups to avoid overfitting in classification problems. These two variants have widened the scope of applicability of PLSDA-batch to different data settings.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("PLSDAbatch")

Details

MaintainerYiwen (Eva) Wang <anjiwangyiwen@gmail.com>
AuthorYiwen (Eva) Wang [aut, cre] (ORCID: <https://orcid.org/0000-0002-7067-9093>), Kim-Anh Le Cao [aut]
LicenseGPL-3
URLhttps://github.com/EvaYiwenWang/PLSDAbatch
Bug Reportshttps://github.com/EvaYiwenWang/PLSDAbatch/issues/
Downloads rank195
Source branchRELEASE_3_23
biocViewsBatchEffect, Classification, DimensionReduction, Microbiome, Normalization, PrincipalComponent, Software, StatisticalMethod, Visualization

Documentation

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Dependencies

Depends: R (>= 4.5.0)

Imports: ggplot2, ggpubr, grid, gridExtra, lmerTest, mixOmics, performance, scales, stats, Rdpack

Suggests: SummarizedExperiment, TreeSummarizedExperiment, vegan, knitr, rmarkdown, BiocStyle, testthat, badger, pheatmap, Biobase