Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb)....
Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors Yu-Jen Lin Arul S. Menon Steven E. Brenner Human Genomics(2024) The contribution of silencer variants to human diseases
Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors Yu-Jen Lin Arul S. Menon Steven E. Brenner Human Genomics (2024) An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases ...
The performance of variant impact prediction methods is hard to assess unambiguously. Independent studies (Chan et al.2007; Dong et al.2015; Ghosh et al.2017; Gunning et al.2020; Leong et al.2015; Li et al.2018; Livesey and Marsh2020; Michels et al.2019; Miosge et al.2015; Suybeng...
Neighborhood-Aware Variant Impact Predictor genomicsvariantsvariant-callingvariant-annotationre-sequencing UpdatedJan 17, 2025 Python gwaseqtlvariant-annotation UpdatedFeb 28, 2022 R GPF: Genotypes and Phenotypes in Families genomicsvariantsvariant-annotation ...
data on the embedding. In addition, we observed that the number of locally maximal clump center cells is at least 1–2 orders of magnitude smaller than the number of cells. Thus, the number of clumps that need to be scored decreases substantially with little impact on accuracy (See below)...
pathogenicity data. We apply this approach, presenting a fast, scalable deep learning predictor, Sequence UNET, and a corresponding python package. It uses a fully convolutional architecture to predict protein PSSMs from wild-type sequence with optional structural input. The model is trained to ...
The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of inter
All data used in this study are already within the public domain, with the exception of the HGMD dataset (https://www.hgmd.cf.ac.uk/ac/index.php), which is a private resource owned by the Institute of Medical Genetics in Cardiff University (requests to access this database should be dir...
When evaluating the impact of age across each variant time period, we found increased odds of adverse outcomes among older patients compared with younger patients across all 3 variant time periods. Last, when continuously modeling age as a predictor of adverse outcomes, we show that increasing age...