Quality control for single-cell analysis of high-plex tissue profiles using CyLinter
Shranjeno v:
| izdano v: | Nature Methods vol. 21, no. 12 (Dec 2024), p. 2248 |
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| Izdano: |
Nature Publishing Group
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| Teme: | |
| Online dostop: | Citation/Abstract Full Text - PDF |
| Oznake: |
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MARC
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| 024 | 7 | |a 10.1038/s41592-024-02328-0 |2 doi | |
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| 245 | 1 | |a Quality control for single-cell analysis of high-plex tissue profiles using CyLinter | |
| 260 | |b Nature Publishing Group |c Dec 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Tumors are complex assemblies of cellular and acellular structures patterned on spatial scales from microns to centimeters. Study of these assemblies has advanced dramatically with the introduction of high-plex spatial profiling. Image-based profiling methods reveal the intensities and spatial distributions of 20–100 proteins at subcellular resolution in 103–107 cells per specimen. Despite extensive work on methods for extracting single-cell data from these images, all tissue images contain artifacts such as folds, debris, antibody aggregates, optical aberrations and image processing errors that arise from imperfections in specimen preparation, data acquisition, image assembly and feature extraction. Here we show that these artifacts dramatically impact single-cell data analysis, obscuring meaningful biological interpretation. We describe an interactive quality control software tool, CyLinter, that identifies and removes data associated with imaging artifacts. CyLinter greatly improves single-cell analysis, especially for archival specimens sectioned many years before data collection, such as those from clinical trials.Microscopy artifacts and tissue imperfections interfere with single-cell analysis. CyLinter software offers quality control for high-plex tissue profiling by removing artifactual cells, thereby facilitating accuracy of biological interpretation. | |
| 653 | |a Clinical trials | ||
| 653 | |a Data acquisition | ||
| 653 | |a Software | ||
| 653 | |a Quality control | ||
| 653 | |a Assemblies | ||
| 653 | |a Image processing | ||
| 653 | |a Spatial distribution | ||
| 653 | |a Artifact identification | ||
| 653 | |a Defects | ||
| 653 | |a Data collection | ||
| 653 | |a Specimen preparation | ||
| 653 | |a Interactive control | ||
| 653 | |a Data processing | ||
| 653 | |a Data analysis | ||
| 653 | |a Impact analysis | ||
| 653 | |a Image acquisition | ||
| 653 | |a Optical data processing | ||
| 653 | |a Image quality | ||
| 653 | |a Cellular structure | ||
| 653 | |a Environmental | ||
| 773 | 0 | |t Nature Methods |g vol. 21, no. 12 (Dec 2024), p. 2248 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3141257616/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3141257616/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |