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MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging.

Denis SchapiroArtem SokolovClarence YappYu-An ChenJeremy L MuhlichJoshua HessAllison L CreasonAjit J NirmalGregory J BakerMaulik K NariyaJia-Ren LinZoltan MaligaConnor A JacobsonMatthew W HodgmanJuha RuokonenSamouil L FarhiDomenic AbbondanzaEliot T McKinleyDaniel PerssonCourtney BettsShamilene SivagnanamAviv RegevJeremy GoecksD Borden LacyLisa M CoussensSandro SantagataPeter Karl Sorger
Published in: Nature methods (2021)
Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.
Keyphrases
  • high resolution
  • single cell
  • deep learning
  • optical coherence tomography
  • induced apoptosis
  • rna seq
  • machine learning
  • signaling pathway
  • cell death
  • electronic health record
  • endoplasmic reticulum stress