Nature Communications (May 2020)

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis

  • Xiangjie Li,
  • Kui Wang,
  • Yafei Lyu,
  • Huize Pan,
  • Jingxiao Zhang,
  • Dwight Stambolian,
  • Katalin Susztak,
  • Muredach P. Reilly,
  • Gang Hu,
  • Mingyao Li

DOI
https://doi.org/10.1038/s41467-020-15851-3
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 14

Abstract

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Increasingly large scRNA-seq datasets demand better and more scalable analysis tools. Here, the authors introduce a scalable unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function and enables removal of batch effects.