MixMC is a tool for pre-processing microbiome data, particularly addressing the challenges of sparse and compositional data. It applies essential steps like adding an offset, pre-filtering low-count features, and performing centered log-ratio (CLR) transformation to make the data suitable for downstream analysis. It’s particularly useful for ensuring accurate results in multivariate analyses like PCA and classification.
R script to run analysis:
Download here
References:
1. Lê Cao KA, Costello ME, Lakis VA, Bartolo F, Chua XY, et al. (2016) MixMC: A Multivariate Statistical Framework to Gain Insight into Microbial Communities. PLOS ONE 11(8): e0160169. doi: 10.1371/journal.pone.0160169
2. Koren O., Spor A., Felin J., Fak F., Stombaugh J., Tremaroli V., et al.: Human oral, gut, and plaque microbiota in patients with atherosclerosis. Proceedings of the National Academy of Sciences 108(Suppl 1), 4592-4598 (2011)
3. Arumugam M., Raes J., Pelletier E., Le Paslier D., Yamada T., Mende D.R., et al.: Enterotypes of the human gut microbiome. Nature 473 (7346), 174–180 (2011)
4. Aitchison, J., 1982. The statistical analysis of compositional data. Journal of the Royal Statistical Society. Series B (Methodological), pp.139-177.
5. Pawlowsky-Glahn V, Egozcue J, Tolosana-Delgado R (2015) Modeling and Analysis of Compositional Data, Wiley
6. Paulson, J. N., Stine, O. C., Bravo, H. C., & Pop, M. (2013). Differential abundance analysis for microbial marker-gene surveys. Nature methods, 10(12), 1200–1202. https://doi.org/10.1038/nmeth.2658