A-G.44: PanelClone: signature-aware subclonal reconstruction that scales with mutation count
Sangwon Um
Taehun Kim
Korea University, College of Medicine
Hyowon Lee
Korea University, College of Medicine
Cheol Soon Lee
Korea University, College of Medicine
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Subclonal reconstruction is essential for understanding tumor evolution and predicting treatment resistance, yet reliable deconvolution has required the hundreds-to-thousands of somatic mutations available only from whole-genome/exome sequencing—leaving clinical deep-panel assays (300–500 genes; 5–50 mutations/sample) underserved. We present PanelClone, a single-sample framework that maximizes subclonal resolution by jointly exploiting two orthogonal signals—variant frequency and mutational signature—and by adapting inference stringency to the available mutation count. PanelClone combines three components. (1) Multiplicity-aware CCF inference with explicit neutral-tail modeling: a beta-binomial mixture corrects for purity and local copy number, marginalizes mutation multiplicity, and models neutral passenger mutations as a truncated 1/f power-law tail, suppressing spurious (“ghost”) subclones. (2) A dual-axis ghost gate: because distinct subclones often arise under distinct mutational processes, PanelClone treats each mutation’s trinucleotide signature as an axis orthogonal to frequency, letting it separate subclones that overlap in CCF and rescue signature-distinct subclones buried in the neutral tail—cases that frequency-only methods (PyClone-VI, MOBSTER) merge or miss and that signature-only methods (CloneSig) over-call. (3) Tiered, mutation-count-adaptive selection: sparse Bayesian (MAP-EM) clustering with automatic cluster-number determination that degrades gracefully from full clustering to binary clonal/subclonal classification to individual-CCF reporting as counts fall. In simulation (BAMSurgeon-style data with injected copy-number, purity and trinucleotide-signature structure), evaluated with SMC-Het metrics (V-measure, CCF MAD, co-clustering), the dual-axis design recovers subclones that frequency-only baselines miss and avoids the over-segmentation of signature-only approaches, with the advantage concentrated where subclones differ in mutational process. Extension to clinical panel scale—including population-based haplotype phasing across panel targets and paired bulk RNA-seq for genome-wide copy-number and allele-specific-expression validation—and benchmarking against matched multi-region cohorts are underway. PanelClone will be made publicly available upon publication.
Co-authors: Sangwon Um, Taehun Kim, Hyowon Lee, Cheol Soon Lee
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