The number of microbiome-related studies has notably increased the availability of data on human microbiome composition and function. These studies provide the essential material to deeply explore host-microbiome associations and their relation to the development and progression of various complex diseases. Improved data-analytical tools are needed to exploit all information from these biological datasets, taking into account the peculiarities of microbiome data, i.e., compositional, heterogeneous and sparse nature of these datasets. The possibility of predicting host-phenotypes based on taxonomy-informed feature selection to establish an association between microbiome and predict disease states is beneficial for personalized medicine. In this regard, machine learning (ML) provides new insights into the development of models that can be used to predict outputs, such as classification and prediction in microbiology, infer host phenotypes to predict diseases and use microbial communities to stratify patients by their characterization of state-specific microbial signatures. Here we review the state-of-the-art ML methods and respective software applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on the application of ML in microbiome studies related to association and clinical use for diagnostics, prognostics, and therapeutics. Although the data presented here is more related to the bacterial community, many algorithms could be applied in general, regardless of the feature type. This literature and software review covering this broad topic is aligned with the scoping review methodology. The manual identification of data sources has been complemented with: (1) automated publication search through digital libraries of the three major publishers using natural language processing (NLP) Toolkit, and (2) an automated identification of relevant software repositories on GitHub and ranking of the related research papers relying on learning to rank approach.

Bioinformatics Research Unit Riga Stradins University Riga Latvia

Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y la Nutrición Instituto de Salud Carlos 3 Madrid Spain

Centro de Matemática e Aplicações FCT UNL Caparica Portugal

Colorectal Cancer Group Institut de Recerca Biomedica de Bellvitge Barcelona Spain

Computational Biology Group Precision Nutrition and Cancer Research Program IMDEA Food Institute Madrid Spain

Consortium for Biomedical Research in Epidemiology and Public Health Barcelona Spain

Department of Biotechnology Institute of Molecular and Cell Biology University of Tartu Tartu Estonia

Department of Clinical Science University of Bergen Bergen Norway

Department of Clinical Sciences Faculty of Medicine University of Barcelona Barcelona Spain

Department of Computer Networks and Systems Silesian University of Technology Gliwice Poland

Department of Computer Science University of Crete Heraklion Greece

Department of Computing University of Turku Turku Finland

Department of Information Systems Zefat Academic College Zefat Israel

Department of Mathematical Analysis and Applications of Mathematics Palacký University Olomouc Czechia

Department of Microbiology University of Innsbruck Innsbruck Austria

EPIUnit Instituto de Saúde Pública da Universidade do Porto Porto Portugal

Faculty of Computer Science and Engineering Ss Cyril and Methodius University Skopje North Macedonia

Faculty of Engineering and Natural Sciences International University of Sarajevo Sarajevo Bosnia and Herzegovina

Faculty of Mathematics and Computer Science Nicolaus Copernicus University Toruń Poland

Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

Galilee Digital Health Research Center Zefat Academic College Zefat Israel

Group for Microbiology and Microbial Biotechnology Department of Animal Science University of Ljubljana Ljubljana Slovenia

Institute of Genomics Estonian Genome Centre University of Tartu Tartu Estonia

Institute of Molecular and Cell Biology University of Tartu Tartu Estonia

NOVA Laboratory for Computer Science and Informatics FCT UNL Caparica Portugal

Oncology Data Analytics Program Catalan Institute of Oncology Barcelona Spain

School of Microbiology and APC Microbiome Ireland University College Cork Cork Ireland

South West University Neofit Rilski Blagoevgrad Bulgaria

Unidad de Gestión Clínica de Endocrinología y Nutrición Instituto de Investigación Biomédica de Málaga Hospital Clínico Universitario Virgen de la Victoria Universidad de Málaga Málaga Spain

Université Paris Saclay INRAE MGP Jouy en Josas France

University Sarajevo School of Science and Technology Sarajevo Bosnia and Herzegovina

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