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

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, MC...

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Main Authors: Schapiro, Denis (Author) , Sokolov, Artem (Author) , Yapp, Clarence (Author) , Chen, Yu-An (Author) , Muhlich, Jeremy L. (Author) , Hess, Joshua (Author) , Creason, Allison L. (Author) , Nirmal, Ajit J. (Author) , Baker, Gregory J. (Author) , Nariya, Maulik K. (Author) , Lin, Jia-Ren (Author) , Maliga, Zoltan (Author) , Jacobson, Connor A. (Author) , Hodgman, Matthew W. (Author) , Ruokonen, Juha (Author) , Farhi, Samouil L. (Author) , Abbondanza, Domenic (Author) , McKinley, Eliot T. (Author) , Persson, Daniel (Author) , Betts, Courtney (Author) , Sivagnanam, Shamilene (Author) , Regev, Aviv (Author) , Goecks, Jeremy (Author) , Coffey, Robert J. (Author) , Coussens, Lisa M. (Author) , Santagata, Sandro (Author) , Sorger, Peter K. (Author)
Format: Article (Journal)
Language:English
Published: 2022
In: Nature methods
Year: 2022, Volume: 19, Issue: 3, Pages: 311-315
ISSN:1548-7105
DOI:10.1038/s41592-021-01308-y
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1038/s41592-021-01308-y
Verlag, lizenzpflichtig, Volltext: https://www.nature.com/articles/s41592-021-01308-y
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Author Notes: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 Betts, Shamilene Sivagnanam, Aviv Regev, Jeremy Goecks, Robert J. Coffey, Lisa M. Coussens, Sandro Santagata and Peter K. Sorger
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Summary: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.
Item Description:Gesehen am 01.06.2022
First published online: 25 November 2021
Physical Description:Online Resource
ISSN:1548-7105
DOI:10.1038/s41592-021-01308-y

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