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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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2022
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| In: |
Nature methods
Year: 2022, Jahrgang: 19, Heft: 3, Pages: 311-315 |
| ISSN: | 1548-7105 |
| DOI: | 10.1038/s41592-021-01308-y |
| Online-Zugang: | 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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| Verfasserangaben: | 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 |
MARC
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| 245 | 1 | 0 | |a MCMICRO |b a scalable, modular image-processing pipeline for multiplexed tissue imaging |c 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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| 520 | |a 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. | ||
| 650 | 4 | |a Image processing | |
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| 650 | 4 | |a Systems biology | |
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| 700 | 1 | |a Lin, Jia-Ren |e VerfasserIn |4 aut | |
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| 700 | 1 | |a Sorger, Peter K. |e VerfasserIn |4 aut | |
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