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Mining Thousands of Genomes to Classify Somatic and Pathogenic Structural Variants

Layer, R. M.; Sedlazeck, F. J.; Pedersen, B. S.; Quinlan, A. R.

2021-04-22 bioinformatics
10.1101/2021.04.21.440844 bioRxiv
Show abstract

Structural variants (SVs) are associated with cancer progression and Mendelian disorders, but challenges with estimating SV frequency remain a barrier to somatic and de novo classification. In particular, variability in filtering and variant calling heuristics limit our ability to use SV catalogs from large cohorts. We present a method to index and search the raw alignments from thousands of samples that overcomes these limitations and supports robust SV analysis.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.