CYCLONE: recycle contrastive learning for integrating single-cell gene expression data.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Combining single-cell transcriptome sequencing results from several batches reduces batch effect, which improves our understanding of cellular identity and function.

Authors

  • Han Ji
    School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan, 430074, China.
  • Xinwei He
    School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan, 430074, China.
  • Hongwei Li
    Department of Informatics, Technische Universität München, Munich, Germany.