Cargando…
Biological relevance of computationally predicted pathogenicity of noncoding variants
Computational prediction of the phenotypic propensities of noncoding single nucleotide variants typically combines annotation of genomic, functional and evolutionary attributes into a single score. Here, we evaluate if the claimed excellent accuracies of these predictions translate into high rates o...
Autores principales: | Liu, Li, Sanderford, Maxwell D., Patel, Ravi, Chandrashekar, Pramod, Gibson, Greg, Kumar, Sudhir |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338804/ https://www.ncbi.nlm.nih.gov/pubmed/30659175 http://dx.doi.org/10.1038/s41467-018-08270-y |
Ejemplares similares
-
TreeMap: a structured approach to fine mapping of eQTL variants
por: Liu, Li, et al.
Publicado: (2020) -
Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants
por: Ose, Nicholas J., et al.
Publicado: (2022) -
Improving cellular phylogenies through the integrated use of mutation order and optimality principles
por: Miura, Sayaka, et al.
Publicado: (2023) -
Bootstrap confidence for molecular evolutionary estimates from tumor bulk sequencing data
por: Huzar, Jared, et al.
Publicado: (2023) -
PINES: phenotype-informed tissue weighting improves prediction of pathogenic noncoding variants
por: Bodea, Corneliu A., et al.
Publicado: (2018)