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

Authors :
Artem Sokolov
Jeremy Goecks
Courtney Betts
Yu-An Chen
Clarence Yapp
Domenic Abbondanza
Ajit J. Nirmal
Samouil L. Farhi
Robert J. Coffey
Lisa M. Coussens
Aviv Regev
Connor A. Jacobson
Jia-Ren Lin
Juha Ruokonen
Denis Schapiro
Shamilene Sivagnanam
Gregory J. Baker
Daniel Persson
Joshua Hess
Peter K. Sorger
Zoltan Maliga
Jeremy L. Muhlich
Eliot T. McKinley
Maulik K. Nariya
Sandro Santagata
Matthew W. Hodgman
Allison L. Creason
Source :
Nat Methods
Publication Year :
2021

Abstract

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. MCMICRO is a modular and open-source computational pipeline for transforming highly multiplexed whole-slide images of tissues into single-cell data. MCMICRO is versatile and can be used with CODEX, mxIF, CyCIF, mIHC and H&E staining data.

Details

ISSN :
15487105
Volume :
19
Issue :
3
Database :
OpenAIRE
Journal :
Nature methods
Accession number :
edsair.doi.dedup.....989aa17e26d8db3260f142116917dd39