An integrative approach to predicting the functional effects of non-coding and coding sequence variation.
Bioinformatics
; 31(10): 1536-43, 2015 May 15.
Article
en En
| MEDLINE
| ID: mdl-25583119
ABSTRACT
MOTIVATION Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source. RESULTS:
We show that our method outperforms current state-of-the-art algorithms, CADD and GWAVA, when predicting the functional consequences of non-coding variants. In addition, FATHMM-MKL is comparable to the best of these algorithms when predicting the impact of coding variants. The method includes a confidence measure to rank order predictions.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Variación Genética
/
Algoritmos
/
Genoma Humano
/
Sistemas de Lectura Abierta
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Regiones no Traducidas
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Anotación de Secuencia Molecular
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2015
Tipo del documento:
Article