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Stochastic variational variable selection for high-dimensional microbiome data.

Tung DangKie KumaishiErika UsuiShungo KoboriTakumi SatoYusuke TodaYuji YamasakiHisashi TsujimotoYasunori IchihashiHiroyoshi Iwata
Published in: Microbiome (2022)
SVVS demonstrates a better performance and significantly faster computation than those of the existing methods in all cases of testing datasets. In particular, SVVS is the only method that can analyze massive high-dimensional microbial data with more than 50,000 microbial species and 1000 samples. Furthermore, a core set of representative microbial species is identified using SVVS that can improve the interpretability of Bayesian mixture models for a wide range of microbiome studies. Video Abstract.
Keyphrases
  • microbial community
  • electronic health record
  • big data
  • cross sectional
  • machine learning
  • case control