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CellSavior: an open-source framework for improved cell calling in targeted single-cell DNA sequencing.
Bioinformatics · · Journal Article
Kim, Chung + more
Abstract ↗AI summary
The abstract is read at the publisher; the summary is JClub's.
CellSavior, an open-source cell calling framework for targeted single-cell DNA sequencing, recapitulates CellFinder annotations in 31 of 33 datasets (93.9%).
- Why it matters: Reliable cell calling is essential because barcode selection determines which signals reflect true cells versus background, shaping all downstream analyses. Existing approaches often use empirical thresholds and vary in performance across datasets, limiting reproducibility.
- What they did: CellSavior uses ensemble clustering across multiple distance metrics with confidence-weighted merging to produce consensus cell classifications, plus an integrated standardized downstream pipeline. It was evaluated on 33 public and in-house scDNA-seq datasets.
- The result: In 31 cases, CellSavior matched CellFinder, and in the remaining discordant datasets it produced more biologically interpretable annotations by rescuing previously undetected clusters enriched for hotspot genomic alterations.
The findingWhy it mattersWhat they didThe result
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