MaAsLin is a multivariate statistical framework that finds associations between clinical metadata and microbial community abundance or function. The clinical metadata can be of any type continuous (for example age and weight), boolean (sex, stool/biopsy), or discrete/factor (cohort groupings and phenotypes). MaAsLin is best used in the case when you are associating many metadata with microbial measurements. When this is the case each metadatum can be a diffrent type. For example, you could include age, weight, sex, cohort and phenotype in the same input file to be analyzed in the same MaAsLin run. The microbial measurements are expected to be normalized before using MaAsLin and so are proportional data ranging from 0 to 1.0.
The results of a MaAsLin run are the association of a specific microbial community member with metadata. These associations are without the influence of the other metadata in the study. There are certain factors known that can influence the microbiome (for example diet, age, geography, fecal or biopsy sample origin). MaAsLin allows one to detect the effect of a metadata, possibly a phenotype, deconfounding the effects of diet, age, sample origin or any other metadata captured in the study |