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

<jats:title>Abstract</jats:title><jats:p>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 de...

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Bibliographic Details
Main Authors: Schapiro, Denis, Sokolov, Artem, Yapp, Clarence, Chen, Yu-An, Muhlich, Jeremy L, Hess, Joshua, Creason, Allison L, Nirmal, Ajit J, Baker, Gregory J, Nariya, Maulik K, Lin, Jia-Ren, Maliga, Zoltan, Jacobson, Connor A, Hodgman, Matthew W, Ruokonen, Juha, Farhi, Samouil L, Abbondanza, Domenic, McKinley, Eliot T, Persson, Daniel, Betts, Courtney, Sivagnanam, Shamilene, Regev, Aviv, Goecks, Jeremy, Coffey, Robert J, Coussens, Lisa M, Santagata, Sandro, Sorger, Peter K
Other Authors: Massachusetts Institute of Technology. Department of Biology
Format: Article
Language:English
Published: Springer Science and Business Media LLC 2023
Online Access:https://hdl.handle.net/1721.1/147096
Description
Summary:<jats:title>Abstract</jats:title><jats:p>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.</jats:p>