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bioRxiv · 10.1101/2020.02.11.943316

mAML: an automated machine learning pipeline with a microbiome repository for human disease classification

Yang, F.·Zou, Q.
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Abstract

Due to the concerted efforts to utilize the microbial features to improve disease prediction capabilities, automated machine learning (AutoML) systems designed to get rid of the tediousness in manually performing ML tasks are in great demand. Here we developed mAML, an ML model-building pipeline, which can automatically and rapidly generate optimized and interpretable models for personalized microbial classification tasks in a reproducible way. The pipeline is deployed on a web-based platform and the server is user-friendly, flexible, and has been designed to be scalable according to the specific requirements. This pipeline exhibits high performance for 13 benchmark datasets including both binary and multi-class classification tasks. In addition, to facilitate the application of mAML and expand the human disease-related microbiome learning repository, we developed GMrepo ML repository (GMrepo Microbiome Learning repository) from the GMrepo database. The repository involves 120 microbial classification tasks for 85 human-disease phenotypes referring to 12,429 metagenomic samples and 38,643 amplicon samples. The mAML pipeline and the GMrepo ML repository are expected to be important resources for researches in microbiology and algorithm developments. Database URLhttp://39.100.246.211:8050/Home

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Yang, F., Zou, Q.. 2020-02-12. mAML: an automated machine learning pipeline with a microbiome repository for human disease classification. https://doi.org/10.1101/2020.02.11.943316

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