lefser is the R implementation of the Python package, Linear discriminant analysis (LDA) Effect Size (LEfSe). LEfSe is the most widely used Python package and Galaxy module for metagenomic biomarker discovery and visualization (Segata et al. 2011). LEfSe utilizes standard statistical significance tests along with supplementary tests that incorporate biological consistency and the relevance of effects to identity the features (e.g., organisms, clades, OTU, genes, or functions) that are most likely to account for differences between the two sample classes of interest, referred as ‘classes’. While LEfSe is widely used and available in different platform such as Galaxy UI and Conda, there is no convenient way to incorporate it in R-based workflows. Thus, we re-implement LEfSe as an R/Bioconductor package, lefser. Following the LEfSe‘s algorithm including Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis, with some modifications, lefser successfully reproduces and improves the original statistical method and the associated plotting functionality.
If you use lefser in published research, please cite:
Asya Khleborodova, Samuel D Gamboa-Tuz, Marcel Ramos, Nicola Segata, Levi Waldron, Sehyun Oh, Lefser: Implementation of metagenomic biomarker discovery tool, LEfSe, in R, Bioinformatics, 2024;, btae707, doi:10.1093/bioinformatics/btae707
A BibTeX entry for LaTeX users is:
@article{10.1093/bioinformatics/btae707,
author = {Khleborodova, Asya and Gamboa-Tuz, Samuel D and Ramos, Marcel and Segata, Nicola and Waldron, Levi and Oh, Sehyun},
title = {Lefser: Implementation of metagenomic biomarker discovery tool, LEfSe, in R},
journal = {Bioinformatics},
pages = {btae707},
year = {2024},
month = {11},
issn = {1367-4811},
doi = {10.1093/bioinformatics/btae707},
url = {https://doi.org/10.1093/bioinformatics/btae707},
eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btae707/60811200/btae707.pdf},
}