lefser

lefser implements the LEfSe method for identifying microbial biomarkers using statistical tests and linear discriminant analysis to discover differences between microbial communities.

Key Features:

• Statistical Testing: Utilizes the Kruskal-Wallis test and Wilcoxon Rank-Sum test for biomarker discovery.
• Linear Discriminant Analysis: Performs Linear Discriminant Analysis for metagenomic biomarker identification.
• R/Bioconductor Integration: Provides comparable functionality within the R/Bioconductor ecosystem of statistical analysis tools.
• Algorithmic Improvements: Includes improvements to the original LEfSe algorithm for performance, accuracy, and reproducibility.

Scientific Applications:

• Metagenomic Biomarker Discovery: Identifies microbial biomarkers from metagenomic datasets.
• Microbial Community Comparison: Discovers differences between microbial communities in human and mouse metagenomic datasets.
• Benchmarking: Enables benchmarking against other metagenomic analysis tools within R workflows.

Methodology:

The method applies the Kruskal-Wallis test, Wilcoxon Rank-Sum test, and Linear Discriminant Analysis, with improvements to the original LEfSe algorithm for performance, accuracy, and reproducibility.