ChainFinder

Overview

ChainFinder is a graph-theory algorithm developed by Baca et al. (2013) to detect “chromoplexy” — chains of interdependent chromosomal rearrangements that arise in a coordinated or near-simultaneous manner. It models structural variants as edges in a graph and identifies chains of translocations and deletions that co-occur across multiple chromosomes more often than expected under an independent model. ChainFinder distinguishes chromoplexy from both random sequential rearrangements and catastrophic chromothripsis by testing statistical independence of breakpoint co-location. It was introduced and applied in a WGS study of 57 prostate tumors and subsequently validated on pan-cancer genomes.

Used by

• Introduced and applied to 57 prostate tumor WGS genomes to detect chromoplexy chains of ≥5 rearrangements (≥10 breakpoints); chains were detected in 50/57 tumors (88%); pan-cancer validation on 59 additional genomes across melanoma, NSCLC, HNSC, and breast adenocarcinoma confirmed chromoplexy is not prostate-specific PMID:23622249

Notes

• Defines chains based on spatial proximity of breakpoints and tests against simulated null distributions (p < 10⁻⁴ threshold used in the original prostate study).
• Distinguishes ETS+ prostate tumors (inter-chromosomal chains linked to transcription hubs) from ETS−/CHD1del tumors (intra-chromosomal chains in late-replicating heterochromatin).
• Requires paired-end WGS with SV calls as input; typically used downstream of dRanger or equivalent callers.

Sources

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