A machine learning framework to determine geolocations from metagenomic profiling.

Journal: Biology direct
Published Date:

Abstract

BACKGROUND: Studies on metagenomic data of environmental microbial samples found that microbial communities seem to be geolocation-specific, and the microbiome abundance profile can be a differentiating feature to identify samples' geolocations. In this paper, we present a machine learning framework to determine the geolocations from metagenomics profiling of microbial samples.

Authors

  • Lihong Huang
    Department of Information Technology, Hunan Women's University, Changsha, Hunan 410002, PR China; College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, PR China. Electronic address: lhhuang@hnu.edu.cn.
  • Canqiang Xu
    Aginome Scientific Pte. Ltd., Xiamen, China.
  • Wenxian Yang
    Aginome Scientific Pte. Ltd., Xiamen, China.
  • Rongshan Yu
    School of Informatics, Xiamen University, Xiamen, China. rsyu@xmu.edu.cn.