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LoRA-TV: read depth profile-based clustering of tumor cells in single-cell sequencing.
- Source :
-
Briefings in Bioinformatics . Jul2024, Vol. 25 Issue 4, p1-12. 12p. - Publication Year :
- 2024
-
Abstract
- Single-cell sequencing has revolutionized our ability to dissect the heterogeneity within tumor populations. In this study, we present LoRA-TV (Low Rank Approximation with Total Variation), a novel method for clustering tumor cells based on the read depth profiles derived from single-cell sequencing data. Traditional analysis pipelines process read depth profiles of each cell individually. By aggregating shared genomic signatures distributed among individual cells using low-rank optimization and robust smoothing, the proposed method enhances clustering performance. Results from analyses of both simulated and real data demonstrate its effectiveness compared with state-of-the-art alternatives, as supported by improvements in the adjusted Rand index and computational efficiency. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DEPTH profiling
*ROBUST optimization
Subjects
Details
- Language :
- English
- ISSN :
- 14675463
- Volume :
- 25
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Briefings in Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 178650353
- Full Text :
- https://doi.org/10.1093/bib/bbae277