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BioinformaticsbioRxiv
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A split-control criterion for few-shot adaptation in single-cell perturbation prediction

Wanli LiangiD, Yabing YangiD, Qiong-Yi Zhang, Jing-Cheng Feng, Qian‐Fei WangiD, Dehua Zou, Jialin TangiD, Yang Liu, Siyuan WangiD, Junwei DuaniD, Yu Bai, Yi-Fang Li, WanYang Sun, Yun-Feng Cao, Rong-Rong He

Abstract

Few-shot adaptation can help or harm single-cell perturbation prediction, but conventional evaluation shares a control estimate between calibration responses and held-out targets. We show how methods carry control error into their predictions and derive its contribution to score inflation. Nested control-depth experiments support inverse-depth scaling of inner-product inflation; correlation inflation also depends on the control noise-to-signal ratio. Independent-control scoring changed the rank of 40 of 52 configuration-dataset entries. We introduce SafeDelta, a split-control criterion that uses calibration data to decide whether to adapt. Across six datasets, mean gated gain was non-negative under the original two-control evaluation. On a deep plate, fixed predictions and decisions retained positive mean gains under three additional independent control references. The same reproducibility principle identified a fibrosis programme that localises to scar in human liver. These results inform adaptation decisions and control-depth planning.

PDFDOI

02 /Specification & Classification

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