Abstract

Untangling the complex variations of microbiome associated with large-scale host phenotypes or environment types challenges the currently available analytic methods. Here, we present tmap, an integrative framework based on topological data analysis for population-scale microbiome stratification and association studies. The performance of tmap in detecting nonlinear patterns is validated by different scenarios of simulation, which clearly demonstrate its superiority over the most commonly used methods. Application of tmap to several population-scale microbiomes extensively demonstrates its strength in revealing microbiome-associated host or environmental features and in understanding the systematic interrelations among their association patterns. tmap is available at https://github.com/GPZ-Bioinfo/tmap.

Details

Title
tmap: an integrative framework based on topological data analysis for population-scale microbiome stratification and association studies
Author
Liao, Tianhua; Wei, Yuchen; Luo, Mingjing; Guo-Ping, Zhao; Zhou, Haokui
Pages
1-19
Section
Method
Publication year
2019
Publication date
2019
Publisher
BioMed Central
ISSN
14747596
e-ISSN
1474760X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2341178717
Copyright
© 2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.