ArticleAmerican journal of human genetics2016
REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants.
Article in American journal of human genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07396285 (UCSF Center for Genome Surgery Biobank and Registry), which is not on this map. Cited by 1,834 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
UCSF Center for Genome Surgery Biobank and Registry
Who cites it
1,834 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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1,774 more citing papers are in PubMed but not listed here.
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Authors and funding
41 authors.
Funding
Abstract
The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10
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