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AnsNGS: An Annotation System to Sequence Variations of Next Generation Sequencing Data for Disease-Related Phenotypes / 대한의료정보학회지
Article in En | WPRIM | ID: wpr-197309
Responsible library: WPRO
ABSTRACT
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/.
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Full text: 1 Index: WPRIM Main subject: Phenotype / Genome, Human / Sequence Analysis, DNA / Fees and Charges / Genomic Structural Variation / High-Throughput Nucleotide Sequencing / Molecular Sequence Annotation Type of study: Health_economic_evaluation Limits: Humans Language: En Journal: Healthcare Informatics Research Year: 2013 Type: Article
Full text: 1 Index: WPRIM Main subject: Phenotype / Genome, Human / Sequence Analysis, DNA / Fees and Charges / Genomic Structural Variation / High-Throughput Nucleotide Sequencing / Molecular Sequence Annotation Type of study: Health_economic_evaluation Limits: Humans Language: En Journal: Healthcare Informatics Research Year: 2013 Type: Article