UniPath : a uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research..
Recent advances in single-cell open-chromatin and transcriptome profiling have created a challenge of exploring novel applications with a meaningful transformation of read-counts, which often have high variability in noise and drop-out among cells. Here, we introduce UniPath, for representing single-cells using pathway and gene-set enrichment scores by a transformation of their open-chromatin or gene-expression profiles. The robust statistical approach of UniPath provides high accuracy, consistency and scalability in estimating gene-set enrichment scores for every cell. Its framework provides an easy solution for handling variability in drop-out rate, which can sometimes create artefact due to systematic patterns. UniPath provides an alternative approach of dimension reduction of single-cell open-chromatin profiles. UniPath's approach of predicting temporal-order of single-cells using their pathway enrichment scores enables suppression of covariates to achieve correct order of cells. Analysis of mouse cell atlas using our approach yielded surprising, albeit biologically-meaningful co-clustering of cell-types from distant organs. By enabling an unconventional method of exploiting pathway co-occurrence to compare two groups of cells, our approach also proves to be useful in inferring context-specific regulations in cancer cells. Available at https://reggenlab.github.io/UniPathWeb/.
| Errataetall: |
ErratumIn: Nucleic Acids Res. 2021 Feb 22;49(3):1801. - PMID 33450029 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:49 |
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| Enthalten in: |
Nucleic acids research - 49(2021), 3 vom: 22. Feb., Seite e13 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Chawla, Smriti [VerfasserIn] |
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Date Completed 03.03.2021 Date Revised 03.03.2021 published: Print ErratumIn: Nucleic Acids Res. 2021 Feb 22;49(3):1801. - PMID 33450029 Citation Status MEDLINE |
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| doi: |
10.1093/nar/gkaa1138 |
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| PPN (Katalog-ID): |
NLM318411725 |
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| 520 | |a © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. | ||
| 520 | |a Recent advances in single-cell open-chromatin and transcriptome profiling have created a challenge of exploring novel applications with a meaningful transformation of read-counts, which often have high variability in noise and drop-out among cells. Here, we introduce UniPath, for representing single-cells using pathway and gene-set enrichment scores by a transformation of their open-chromatin or gene-expression profiles. The robust statistical approach of UniPath provides high accuracy, consistency and scalability in estimating gene-set enrichment scores for every cell. Its framework provides an easy solution for handling variability in drop-out rate, which can sometimes create artefact due to systematic patterns. UniPath provides an alternative approach of dimension reduction of single-cell open-chromatin profiles. UniPath's approach of predicting temporal-order of single-cells using their pathway enrichment scores enables suppression of covariates to achieve correct order of cells. Analysis of mouse cell atlas using our approach yielded surprising, albeit biologically-meaningful co-clustering of cell-types from distant organs. By enabling an unconventional method of exploiting pathway co-occurrence to compare two groups of cells, our approach also proves to be useful in inferring context-specific regulations in cancer cells. Available at https://reggenlab.github.io/UniPathWeb/ | ||
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| 700 | 1 | |a Kong, Say Li |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Zhengwei |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Zhenxun |e verfasserin |4 aut | |
| 700 | 1 | |a Tam, Wai Leong |e verfasserin |4 aut | |
| 700 | 1 | |a Sengupta, Debarka |e verfasserin |4 aut | |
| 700 | 1 | |a Kumar, Vibhor |e verfasserin |4 aut | |
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