A-G.15: Genome wide eccDNA hotspot propensity estimation from confounder aware features
Studying extrachromosomal circular DNA (eccDNA and ecDNA) can reveal genome instability and regulatory change, especially in cancer
disease. Interpreting genome wide recurrence is difficult because apparent hotspots can be inflated by technical and genomic confounders,
including low mappability, repeats, and segmental duplications. We therefore move from classifying individual circles to a locus propensity view
and learn to rank genomic windows using interpretable context features, while using technical tracks only for filtering and diagnostics. We score
recurrence across public experiments from CircleBase v2 in fixed 25 kb bins. For each bin we compute replicate support, defined as the number
of independent experiments (unique PubMed ID and assay) that report at least one overlapping eccDNA interval. To define a fair baseline,
we keep the number and sizes of eccDNA intervals from each experiment fixed, but randomly shuffle their genomic positions within the same
chromosome many times. We then measure how often each bin would be supported under these randomized placements and use the average
as the expected background support. Comparing observed support to this baseline provides a measure of the continuous enrichment score used
for regression and genome wide ranking tasks. The proposed approach was evaluated along two axes: (i) recovery and tail prioritization of
the continuous enrichment signal (random-split = 0.711 ± 0.004, Lift@1% 38, chromosome holdout 0.51, with telomere/centromere
ablations probing positional reliance) and (ii) matched comparison to sequence-only methods via the DeepCircle 1 kb balanced classification
protocol, where we obtain competitive performance.
Co-authors: Delfina Malandrino, Daniele Salerno, Alessia Ture, Rocco Zaccagnino
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