Disease-causing variant recommendation system for clinical genome interpretation with adjusted scores for artefactual variants
Kim, H. H.; Woo, J.; Kim, D.-W.; Lee, J.; Seo, G. H.; Lee, H.; Lee, K.
Show abstract
BackgroundIn the process of finding the causative variant of rare diseases (RD), accurate assessment and prioritization of genetic variants is essential. Although quality control (QC) of genetic variants is strictly performed, the presence of artefactual variants in the remaining set of variants can deteriorate the process. Variant QC and prioritization have been treated as separate processes, leading to limited efficiency and risk of misdiagnosis. ResultsWe developed a disease-causing variant recommendation system that integrates quality control into variant prioritization by adjusting scores for artefactual variants. We confirmed that the QC-related features of the variants contribute to a significant performance improvement. For genomic data from 2,878 patients with rare disorders, the recall rate of finding causative variants was 0.961 for the top 5 ranked variants. We also found that our system recognized the anomaly of QC-related features, so that the scores of artifactual variants to be disease-causing were assessed relatively low. ConclusionsIntegration of variant QC and prioritization help reduce the risk of misdiagnosis based on artefactual variants and increase the effectiveness of clinical genome interpretation.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders 96%
- GeneTerpret: a customizable multilayer approach to genomic variant prioritization and interpretation 95%
- Genome-wide survey of tandem repeats by nanopore sequencing shows that disease-associated repeats are more polymorphic in the general population 93%
Similar papers in this journal
- Cancer SIGVAR: A semi-automated interpretation tool for germline variants of hereditary cancer-related genes 96%
- REVEL is better at predicting pathogenicity of loss-of-function than gain-of-function variants 94%
- Using single molecule Molecular Inversion Probes as a cost-effective, high-throughput sequencing approach to target all genes and loci associated with macular diseases 94%
Similar papers in this journal
- GenOtoScope: Towards automating ACMG classification of variants associated with congenital hearing loss 96%
- Variant calling tool evaluation for variable size indel calling from next generation whole genome and targeted sequencing data 95%
- VarSCAT: A computational tool for sequence context annotations of genomic variants 95%
"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.