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DANCE: a deep learning library and benchmark platform for single-cell analysis.

Jiayuan DingRenming LiuHongzhi WenWenzhuo TangZhaoheng LiJulian VenegasRunze SuDylan MolhoWei JinYixin WangQiaolin LuLingxiao LiWangyang ZuoYi ChangYuying XieJiliang Tang
Published in: Genome biology (2024)
DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts, such as using only one command line. In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to facilitate their own model development. DANCE is an open-source Python package that welcomes all kinds of contributions.
Keyphrases
  • deep learning
  • single cell
  • rna seq
  • high throughput
  • machine learning
  • working memory
  • artificial intelligence