Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical specificities of the data (e.g., sparse, over-dispersed, compositional, inter-variable dependency). This mini review explores preprocessing and transformation methods applied in recent human microbiome studies to address microbiome data analysis challenges. Our results indicate a limited adoption of transformation methods targeting the statistical characteristics of microbiome sequencing data. Instead, there is a prevalent usage of relative and normalization-based transformations that do not specifically account for the specific attributes of microbiome data. The information on preprocessing and transformations applied to the data before analysis was incomplete or missing in many publications, leading to reproducibility concerns, comparability issues, and questionable results. We hope this mini review will provide researchers and newcomers to the field of human microbiome research with an up-to-date point of reference for various data transformation tools and assist them in choosing the most suitable transformation method based on their research questions, objectives, and data characteristics.

BioSense Institute University of Novi Sad Novi Sad Serbia

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

Department of Animal Science Biotechnical Faculty University of Ljubljana Ljubljana Slovenia

Department of Applied Mathematics Faculty of Natural Sciences University of Tirana Tirana Albania

Department of Automation Biocybernetics and Robotics Jožef Stefan Institute Ljubljana Slovenia

Department of Biology Faculty of Natural Sciences University of Tirana Tirana Albania

Department of Biomedical Sciences National Research Council Institute for Biomedical Technologies Bari Italy

Department of Catalysis and Chemical Reaction Engineering National Institute of Chemistry Ljubljana Slovenia

Department of Clinical Science University of Bergen Bergen Norway

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

Department of Mathematics Center for Mathematics and Applications NOVA School of Science and Technology Caparica Portugal

Faculty of Civil and Geodetic Engineering Institute of Sanitary Engineering Ljubljana Slovenia

INRAE MetaGenoPolis Université Paris Saclay Jouy en Josas France

UNIDEMI Department of Mechanical and Industrial Engineering NOVA School of Science and Technology Caparica Portugal

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