A Statistical Framework for Mapping Risk Genes from De Novo Mutations in Whole-Genome-Sequencing Studies.
Am J Hum Genet
; 102(6): 1031-1047, 2018 06 07.
Article
en En
| MEDLINE
| ID: mdl-29754769
ABSTRACT
Analysis of de novo mutations (DNMs) from sequencing data of nuclear families has identified risk genes for many complex diseases, including multiple neurodevelopmental and psychiatric disorders. Most of these efforts have focused on mutations in protein-coding sequences. Evidence from genome-wide association studies (GWASs) strongly suggests that variants important to human diseases often lie in non-coding regions. Extending DNM-based approaches to non-coding sequences is challenging, however, because the functional significance of non-coding mutations is difficult to predict. We propose a statistical framework for analyzing DNMs from whole-genome sequencing (WGS) data. This method, TADA-Annotations (TADA-A), is a major advance of the TADA method we developed earlier for DNM analysis in coding regions. TADA-A is able to incorporate many functional annotations such as conservation and enhancer marks, to learn from data which annotations are informative of pathogenic mutations, and to combine both coding and non-coding mutations at the gene level to detect risk genes. It also supports meta-analysis of multiple DNM studies, while adjusting for study-specific technical effects. We applied TADA-A to WGS data of â¼300 autism-affected family trios across five studies and discovered several autism risk genes. The software is freely available for all research uses.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Estadística como Asunto
/
Mapeo Cromosómico
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Predisposición Genética a la Enfermedad
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Secuenciación Completa del Genoma
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Mutación
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
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Risk_factors_studies
/
Systematic_reviews
Límite:
Humans
Idioma:
En
Revista:
Am J Hum Genet
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos