Protein velocity and acceleration from single-cell multiomics experiments
Abstract The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that le...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2020-02-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13059-020-1945-3 |
| _version_ | 1818032983741825024 |
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| author | Gennady Gorin Valentine Svensson Lior Pachter |
| author_facet | Gennady Gorin Valentine Svensson Lior Pachter |
| author_sort | Gennady Gorin |
| collection | DOAJ |
| description | Abstract The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states. We apply the model to six datasets and demonstrate consistency among cell landscapes and phase portraits. The analysis software is available as the protaccel Python package. |
| first_indexed | 2024-12-10T06:16:02Z |
| format | Article |
| id | doaj.art-747b3b6e3e4d4723864d2677b18a2836 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-10T06:16:02Z |
| publishDate | 2020-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-747b3b6e3e4d4723864d2677b18a28362022-12-22T01:59:26ZengBMCGenome Biology1474-760X2020-02-012111610.1186/s13059-020-1945-3Protein velocity and acceleration from single-cell multiomics experimentsGennady Gorin0Valentine Svensson1Lior Pachter2Division of Chemistry and Chemical Engineering, California Institute of TechnologyDivision of Biology and Biological Engineering & Department of Computing and Mathematical Sciences, California Institute of TechnologyDivision of Biology and Biological Engineering & Department of Computing and Mathematical Sciences, California Institute of TechnologyAbstract The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states. We apply the model to six datasets and demonstrate consistency among cell landscapes and phase portraits. The analysis software is available as the protaccel Python package.http://link.springer.com/article/10.1186/s13059-020-1945-3Protein accelerationProtein velocityRNA velocityTranscriptomicsMultiomicsBioinformatics |
| spellingShingle | Gennady Gorin Valentine Svensson Lior Pachter Protein velocity and acceleration from single-cell multiomics experiments Genome Biology Protein acceleration Protein velocity RNA velocity Transcriptomics Multiomics Bioinformatics |
| title | Protein velocity and acceleration from single-cell multiomics experiments |
| title_full | Protein velocity and acceleration from single-cell multiomics experiments |
| title_fullStr | Protein velocity and acceleration from single-cell multiomics experiments |
| title_full_unstemmed | Protein velocity and acceleration from single-cell multiomics experiments |
| title_short | Protein velocity and acceleration from single-cell multiomics experiments |
| title_sort | protein velocity and acceleration from single cell multiomics experiments |
| topic | Protein acceleration Protein velocity RNA velocity Transcriptomics Multiomics Bioinformatics |
| url | http://link.springer.com/article/10.1186/s13059-020-1945-3 |
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