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Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge.

Runzhi ZhangAlejandro R WalkerSusmita Datta
Published in: Biology direct (2021)
The results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which could be used to identify the sample origins. This was also supported by the results from ANCOM and importance score from the RF. In addition, the accuracy of the prediction could be improved by more samples and better sequencing depth.
Keyphrases
  • machine learning
  • deep learning
  • electronic health record
  • single cell
  • big data
  • optical coherence tomography
  • data analysis