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

Denis Schapiro, Artem Sokolov, Clarence Yapp, Yu An Chen, Jeremy L. Muhlich, Joshua Hess, Allison L. Creason, Ajit J. Nirmal, Gregory J. Baker, Maulik K. Nariya, Jia Ren Lin, Zoltan Maliga, Connor A. Jacobson, Matthew W. Hodgman, Juha Ruokonen, Samouil L. Farhi, Domenic Abbondanza, Eliot T. McKinley, Daniel Persson, Courtney BettsShamilene Sivagnanam, Aviv Regev, Jeremy Goecks, Robert J. Coffey, Lisa M. Coussens, Sandro Santagata, Peter K. Sorger

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)311-315
Number of pages5
JournalNature Methods
Issue number3
StatePublished - Mar 2022

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology


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