Rough Set Microbiome Characterisation

• DOI: 10.48550/arxiv.2105.03903
• Publication Date: 2021-01-01
• Authors: Benjamin Wingfield; Sonya Coleman; T.M. McGinnity; Anthony J. Bjourson
• Keywords: 0301 basic medicine; 0303 health sciences; 03 medical and health sciences; FOS: Biological sciences; Quantitative Biology - Quantitative Methods; Quantitative Methods (q-bio.QM); 3. Good health

Microbiota profiles measure the structure of microbial communities in a defined environment (known as microbiomes). In past decade, microbiome research has focused on health applications result which gut been implicated development broad range diseases such obesity, inflammatory bowel disease, and major depressive disorder. A key goal many experiments is to characterise or describe community. High-throughput sequencing used generate microbiota profiles, but data gathered via this method are extremely challenging analyse, violate multiple strong assumptions standard models. Rough Set Theory (RST) weak that less likely be violated, offers attractive tools for extracting knowledge from complex data. paper we present first application RST characterising microbiomes. We begin with demonstrative benchmark profile extend approach microbiomes depressed subjects enable discovery. find capable excellent characterisation identifying previously undescribed alterations microbiome-gut-brain axis. An important aspect it provides possible solution an open question regarding search optimal normalisation census data, one does not currently exist.