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bioRxiv · 10.1101/2020.04.24.060202

Leveraging a WGS compression and indexing format with dynamic graph references to call structural variants.

English, A. C.·McCarthy, N.·Flickenger, R.·Maheshwari, S.·Meed, L.·Mangubat, A.·Shekar, S. N.
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Abstract

We introduce a novel structural variant calling pipeline (BioGraph) that leverages a read compression and indexing format to discover alleles, assess their supporting coverage, and assign useful quality scores. To evaluate BioGraphs performance, we run five sequencing replicates of the individual HG002 through the BioGraph variant calling pipeline, as well as two other short-read sv-calling pipelines. BioGraph detects the GIAB benchmark SVs at a peak sensitivity of {approx}59% compared to {approx}42% sensitivity from the other pipelines. The overall precision of BioGraph is lower than other pipelines ({approx}81% and {approx}90%, respectively), however, adjusting for quality score, BioGraph calls were sensitive to a greater number of SV calls given the same false discovery rate compared to the other pipelines. Cumulatively {approx}77% of GIAB benchmark SVs are discovered by BioGraph in at least one replicate. After merging discovered calls and running BioGraph Coverage to create a squared-off project-level VCF, we find {approx}90% percent of discovered true positive alleles have at least 5x coverage in all replicates, thus increasing per-replicate recall of alleles having at least 1x coverage to {approx}76.9%.

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English, A. C., McCarthy, N., Flickenger, R., Maheshwari, S., Meed, L., Mangubat, A., Shekar, S. N.. 2020-04-25. Leveraging a WGS compression and indexing format with dynamic graph references to call structural variants.. https://doi.org/10.1101/2020.04.24.060202

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