HIGHLIGHTS
- who: Shaya Akbarinejad from the Department of Computer, Sharif University Tehran, Iran have published the Article: SVNN: an efficient PacBio-specific pipeline for structural variations calling using neural networks, in the Journal: (JOURNAL)
- what: Since prohibitive costs of using high-coverage data have impeded long-read applications with SVNN the authors provide the users with a much faster structural variation detection platform for PacBio reads with high precision and sensitivity in lowcoverage scenarios. This means on real data, which the model has not seen, SVNN achieves 20 percentage points improvement in accuracy compared to NGMLR . . .
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