EvaYiwenWang/PLSDAbatch: PLSDA-batch

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.

Getting started

Package details

Bioconductor views BatchEffect Classification DimensionReduction Microbiome Normalization PrincipalComponent StatisticalMethod Visualization
URL https://github.com/EvaYiwenWang/PLSDAbatch
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
EvaYiwenWang/PLSDAbatch documentation built on Jan. 19, 2024, 11:19 p.m.