bioRxivBioinformaticsPreprint
Transcriptomic similarity guides source selection beyond tissue lineage
Li JiangiD, Jiahong Pang, Bote Luo, Xiai WuiD, Xin LiiD, Haojun ZhangiD
Abstract
Perturbational and pharmacogenomic maps remain incomplete across cellular contexts, leaving a practical source-selection question before response prediction: which measured context should inform an unmeasured target? We tested whether baseline transcriptomic similarity ranks candidate sources for held-out targets, separating source ranking from aggregation and transfer-uncertainty decisions. Similarity tracked matched-response concordance in LINCS and GSE306429; selected-source utility exceeded random expectation in GSE306429 ({Delta}U = 0.034; P = 0.002) and in exact-time-matched MIX-Seq tasks ({Delta}U = 0.046). In the full GDSC2 analysis, the drug-balanced ranking effect was 0.359 (95% CI, 0.337-0.383). In a lineage-restricted analysis of the same eligible subset, within-tissue ranking remained positive at 0.130 (95% CI, 0.119-0.141), retaining 35.8% of the same-subset global effect (0.363; 95% CI, 0.342-0.386). Global transcriptomic top-1 selection exceeded tissue-matched random selection by 0.154 (95% CI, 0.143-0.164). Thus, baseline similarity adds source-ranking information after tissue matching in the evaluated setting, while ranking alone does not resolve whether to aggregate sources or how to quantify transfer uncertainty.
- assay: bulk RNA-seq
- research focus: benchmarking
- research focus: differential expression
- research focus: cell type annotation
- research focus: clustering
- approach: statistical model
- approach: benchmark study
- Citations
- 0
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