… scalability to process big genomic data, particularly when annotating whole-genome sequencing
variants … genome-scale variants in large and complex functional annotation resources. …

… In recent years, population-scale sequencing projects have unveiled tens of … functionality
predictions from missense variants to also include synonymous variants, as well as noncoding …

… ], a population-level metric important for prioritizing population … non-coding variants. We
noted that no methods yielded satisfactory prediction results for rare somatic non-coding variants…

… prediction of the phenotypic propensities of noncoding single nucleotide variants typically
combines annotation of genomic, functional … variant population frequency and predicted impact …

… to calculate functional effect scores of non-coding variants based on the learned functional
patterns. We aimed to evaluate how well DVAR can predict non-coding variants that are …

… de novo variants and variants that have arisen and become fixed in human populations since
the … and deleterious alleles, while the latter are overwhelmingly neutral (or, at most, weakly …

… Here, we focus on data from 108 genomes sampled from the Yoruba population (YRI),
but … additional functional genomic information also does little to improve our predictions (Appendix …

… [13]; PAFA was the first method to introduce the fixation index [33], a population level metric
important for prioritizing population relevant functional non-coding variants [30]. Given that …

… over diverse variant annotations and uses random forest models to prioritize functional
SVs. … with known pathogenic, rare population and somatic cancer variants. This approach is …

… Here we train a machine learning model using functional, mutational and structural features,
… to identify deleterious variants in non-coding regions. We assess the model for functional …