MaAsLin3(Microbiome Multivariable Association with Linear Models) is the latest iteration of the tool's framework. It is designed to determine associations between microbial features (e.g., taxonomic compositions, functional profiles) and metadata (e.g., clinical or environmental variables). MaAsLin3 focuses on flexibility, speed, and improved model fitting.

If you use the MaAsLin2 tool, please cite the reference manuscript:

Nickols WA, Kuntz T, Shen J, Maharjan S, Mallick H, Franzosa EA, Thompson KN, Nearing JT, Huttenhower C. MaAsLin 3: Refining and extending generalized multivariable linear models for meta-omic association discovery.
bioRxiv, 2024.12.13.628459; doi: https://doi.org/10.1101/2024.12.13.628459

Microbiome Association Detection with MaAsLin3

MaAsLin3 is a powerful R-based framework designed for multivariable association studies between microbiome features (e.g., taxa, pathways) and metadata variables. Building on the success of MaAsLin2, MaAsLin3 offers enhanced performance, greater flexibility in modeling, and improved stability. Using various normalization and transformation methods, as well as multiple modeling approaches (e.g., linear, CPLM, zero-inflation), it efficiently identifies meaningful associations while controlling for confounding factors and handling complex data structures.

Through the CosmosID-HUB, researchers can easily upload their data, configure parameters, and run MaAsLin3, then interpret results via automatically generated tables, heatmaps, and summary files—ultimately streamlining the discovery of significant microbiome–metadata relationships.

MaAsLin2 workflow two inputs, which are generated in the CosmosID-HUB:

Profiling Data (feature table)

A table where rows represent samples and columns represent microbial features (e.g., species, genes, pathways). Each cell in the table provides the abundance of that feature in that sample. MaAsLin3 can take raw counts or relative abundances as input. This is the default output of a comparative analysis within the CosmosID-HUB.

Metadata

Metadata that describes is required for this analysis, and tutorials on metadata input can be found here.

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Running the MaAsLin3 Workflow

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Viewing and Interpreting MaAsLin3 Results