arXiv：cs.LG· Arjun Bhupatiraju, Abhiram Bhupatiraju·· 3 小时前
FateMultiplicity：单细胞轨迹推断中的预测多重性与无标签 Rashomon 集
Predictive Multiplicity in Cell-Fate Assignment: Label-Free Rashomon Sets and the Limits of Per-Cell Certification
AI 导读
FateMultiplicity 是一个无需谱系标签即可构建 Rashomon 集的框架，通过交叉拟合留出基因上的非劣性检验评估模型差异。多重性程度更多取决于模型空间多样性而非规模：第二算法 12 种配置暴露 20.0% 细胞存在命运冲突，第一算法 24 种配置仅 3.8%。逐细胞认证边界 FM 未能优于拟合模型自身置信度，在模拟真实标签上 AUC 仅 0.682，低于基线的 0.965。
正文
Abstract:Single-cell trajectory inference maps transcriptomic measurements onto developmental continua, yet configurations that fit the data equally well can assign conflicting cell fates. FateMultiplicity is a label-free framework that constructs a statistically admissible model set, or Rashomon set, without lineage labels, by evaluating model discrepancy on cross-fitted held-out genes under non-inferiority testing calibrated against random-seed variation. Multiplicity is large and depends more on the diversity of the model space than its size: twelve configurations of a second algorithm expose 20.0% of cells where twenty-four of the first expose 3.8%. Whether the per-cell certified fate margin FM yields more reliable assignments than the fitted model already provides is then tested, and it does not. On simulation ground truth, on the same cells, FM discriminates misassignment at AUC 0.682, against 0.965 for the baseline configuration's own decision margin (p = 0.003) and 0.854 for a seed-dispersion baseline. Informativeness is governed by the breadth of the admitted set, not its cardinality: at cardinality four, seed refits give 0.933 and hyperparameter-perturbed sets 0.701. Relaxing the infimum to a q-quantile recovers discrimination but converges toward the single model's own confidence; the supremum reaches 0.973 because theta*'s membership bounds it from below, while the infimum is unanchored. Multiplicity in trajectory inference is worth measuring and reporting, but per-cell certification over a label-free Rashomon set is not a route to more reliable fate calls. Two constructions survive: a margin-erosion ratio separates real from spurious branch points in simulation (AUC 0.890, untested on real data), and against clonally observed fate, uncertified cells disagree with their clone's outcome 16.4 percentage points more often than certified cells (p < 0.001).
| Comments: | 14 pages |
| Subjects: | Machine Learning (cs.LG); Genomics (q-bio.GN) |
| Cite as: | arXiv:2610.11185 [cs.LG] |
| (or arXiv:2610.11185v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11185 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Abhiram Bhupatiraju [view email]
[v1]
Thu, 8 Oct 2026 03:43:28 UTC (1,092 KB)
来源：arXiv：cs.LG · arxiv.org