MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging
Name
s41592-021-01308-y.pdf
Description
Published version
Size
2.93 MB
Format
Adobe PDF
Checksum (MD5)
0834285c329d2048f79f972f295c511f
Author(s)
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
Date Issued
2022
Journal
Nature Methods
Publisher
Springer Science and Business Media LLC
Citation
Schapiro, Denis, Sokolov, Artem, Yapp, Clarence, Chen, Yu-An, Muhlich, Jeremy L et al. 2022. "MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging." Nature Methods, 19 (3).
Version
Final published version
Abstract
AbstractHighly 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.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/S41592-021-01308-Y
