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AnsNGS: An Annotation System to Sequence Variations of Next Generation Sequencing Data for Disease-Related Phenotypes

OBJECTIVES: Next-generation sequencing (NGS) data in the identification of disease-causing genes provides a promising opportunity in the diagnosis of disease. Beyond the previous efforts for NGS data alignment, variant detection, and visualization, developing a comprehensive annotation system suppor...

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Detalles Bibliográficos
Autores principales: Na, Young-Ji, Cho, Yonglae, Kim, Ju Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3633172/
https://www.ncbi.nlm.nih.gov/pubmed/23626918
http://dx.doi.org/10.4258/hir.2013.19.1.50
Descripción
Sumario:OBJECTIVES: Next-generation sequencing (NGS) data in the identification of disease-causing genes provides a promising opportunity in the diagnosis of disease. Beyond the previous efforts for NGS data alignment, variant detection, and visualization, developing a comprehensive annotation system supported by multiple layers of disease phenotype-related databases is essential for deciphering the human genome. To satisfy the impending need to decipher the human genome, it is essential to develop a comprehensive annotation system supported by multiple layers of disease phenotype-related databases. METHODS: AnsNGS (Annotation system of sequence variations for next-generation sequencing data) is a tool for contextualizing variants related to diseases and examining their functional consequences. The AnsNGS integrates a variety of annotation databases to attain multiple levels of annotation. RESULTS: The AnsNGS assigns biological functions to variants, and provides gene (or disease)-centric queries for finding disease-causing variants. The AnsNGS also connects those genes harbouring variants and the corresponding expression probes for downstream analysis using expression microarrays. Here, we demonstrate its ability to identify disease-related variants in the human genome. CONCLUSIONS: The AnsNGS can give a key insight into which of these variants is already known to be involved in a disease-related phenotype or located in or near a known regulatory site. The AnsNGS is available free of charge to academic users and can be obtained from http://snubi.org/software/AnsNGS/.