Nucleic Acids ResearchGenomicsPeer-reviewed journal article
UniPath: A uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles.
Smriti Chawla, Sudhagar Samydurai, Say Li Kong, Zhengwei WuiD, Zhenxun WangiD, Wai Leong TamiD, Debarka SenguptaiD, Vibhor KumariD
Abstract
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. Besides being robust to variability in dropout, UniPath provides consistency and scalability in estimating gene-set enrichment scores for every cell. UniPaths approach of predicting temporal-order of single-cells using their gene-set activity score enables suppression of known covariates. UniPath based analysis of mouse cell atlas yielded surprising, albeit biologically-meaningful co-clustering of cell-types from distant organs and helped in annotating many unlabeled cells. By enabling unconventional analysis, UniPath also proves to be useful in inferring context-specific regulation in cancer cells.
- organism: mouse
- assay: scRNA-seq
- assay: ATAC-seq
- research focus: clustering
- research focus: cell type annotation
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 16
- FWCI
- 0.89
- Field percentile
- top 29%
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