Variant classification guidelines for animals to objectively evaluate genetic variant pathogenicity
Boeykens, F.; Abitbol, M.; Anderson, H.; Casselman, I.; Dufaure de Citres, C.; Hayward, J. J.; Häggström, J.; Kittleson, M. D.; Lepri, E.; Ljungvall, I.; Longeri, M.; Lyons, L. A.; Ohlsson, A.; Peelman, L.; Smets, P.; Vezzosi, T.; van Steenbeek, F.; Broeckx, B. J. G.
Show abstract
Assessing the pathogenicity of a disease-associated variant in animals accurately is vital, both on a population and individual scale. At the population level, breeding decisions based on invalid DNA tests can lead to the incorrect exclusion of animals and compromise the long- term health of a population, and at the level of the individual animal, lead to incorrect treatment and even life-ending decisions. Criteria to determine pathogenicity are not standardized, hence no guidelines for animal variants are available. Here, we developed and optimized the animal variant classification guidelines, based on those developed for humans by The American College of Medical Genetics and Genomics, and demonstrated a superior classification in animals. We described methods to develop datasets for benchmarking the criteria and identified the most optimal in silico variant effect predictor tools. As the reproducibility was high, we classified 72 known disease-associated variants in cats and 40 other disease-associated variants in eight additional species.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Towards robust clinical genome interpretation: developing a consistent terminology to characterize disease-gene relationships - allelic requirement, inheritance modes and disease mechanisms 94%
- Evaluation of Bayesian Classification Framework on the Variant Classification of Hereditary Cancer Predisposition Genes 93%
- Specification of frequency criteria for secondary findings genes to improve variant classification concordance 93%
Similar papers in this journal
- Using single molecule Molecular Inversion Probes as a cost-effective, high-throughput sequencing approach to target all genes and loci associated with macular diseases 93%
- Structure-informed classification of RyR1 variants highlights limitations of current predictors and enables clinical interpretation 93%
- AutoPVS1: An automatic classification tool for PVS1 interpretation of null variants 93%
Similar papers in this journal
- Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci 92%
- Tumor Patterns and Cancer Risk in Carriers of TP53 exonic Germline Variants that alter mRNA Splicing 91%
- Structural variant calling and clinical interpretation in 6224 unsolved rare disease exomes 91%
Similar papers in this journal
- Evidence-based calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for clinical use of PP3/BP4 criteria 94%
- Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel 93%
- Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data 93%
Similar papers in this journal
- Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework 93%
- Recommendations for clinical interpretation of variants found in non-coding regions of the genome 92%
- Evaluating Genome Sequencing Strategies: Trio, Singleton, and Standard Testing in Rare Disease Diagnosis 92%
"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.