Compositional data network analysis via lasso penalized D-trace loss.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: With the development of high-throughput sequencing techniques for 16S-rRNA gene profiling, the analysis of microbial communities is becoming more and more attractive and reliable. Inferring the direct interaction network among microbial communities helps in the identification of mechanisms underlying community structure. However, the analysis of compositional data remains challenging by the relative information conveyed by such data, as well as its high dimensionality.

Authors

  • Huili Yuan
    School of Mathematical Sciences, Peking University, Beijing, China.
  • Shun He
    School of Mathematical Sciences, Peking University, Beijing, China.
  • Minghua Deng
    Center for Quantitative Biology, Peking University, Beijing, China. dengmh@pku.edu.cn.