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Computational Approaches for Unraveling the Effects of Variation in the Human Genome and Microbiome

Authors :
Yanran Wang
Chengsheng Zhu
Zishuo Zeng
Yannick Mahlich
Maximilian Miller
Yana Bromberg
Ariel Aptekmann
Source :
Annual Review of Biomedical Data Science. 3:411-432
Publication Year :
2020
Publisher :
Annual Reviews, 2020.

Abstract

The past two decades of analytical efforts have highlighted how much more remains to be learned about the human genome and, particularly, its complex involvement in promoting disease development and progression. While numerous computational tools exist for the assessment of the functional and pathogenic effects of genome variants, their precision is far from satisfactory, particularly for clinical use. Accumulating evidence also suggests that the human microbiome's interaction with the human genome plays a critical role in determining health and disease states. While numerous microbial taxonomic groups and molecular functions of the human microbiome have been associated with disease, the reproducibility of these findings is lacking. The human microbiome–genome interaction in healthy individuals is even less well understood. This review summarizes the available computational methods built to analyze the effect of variation in the human genome and microbiome. We address the applicability and precision of these methods across their possible uses. We also briefly discuss the exciting, necessary, and now possible integration of the two types of data to improve the understanding of pathogenicity mechanisms.

Details

ISSN :
25743414
Volume :
3
Database :
OpenAIRE
Journal :
Annual Review of Biomedical Data Science
Accession number :
edsair.doi...........0329783798e398e2bda650faa6cbb24c
Full Text :
https://doi.org/10.1146/annurev-biodatasci-030320-041014