leylabmpi/endoR
Code and manual of the endoR R-package (Ruaud et al, in preparation).
This tool helps microbiome scientists understand how complex machine learning models predict outcomes based on microbial data. You feed it a pre-trained tree ensemble model and your original microbiome dataset. It then generates an interpretable network and importance scores showing which microbial taxa or genomic content, and their interactions, are most influential in the model's predictions. This allows researchers to gain insights into microbial associations with host phenotypes.
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Use this if you are a microbiome scientist struggling to interpret your tree ensemble machine learning model's predictions and want to visualize the key microbial features and interactions driving those predictions.
Not ideal if you are not working with tree ensemble models or microbiome data, or if you primarily need to build predictive models rather than interpret existing ones.
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GPL-3.0
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Oct 12, 2023
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