title: AnsNGS: An Annotation System to Sequence Variations of Next Generation Sequencing Data for Disease-Related Phenotypes.
abstract: OBJECTIVE
  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/.
authors.affiliation: Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea. ; Systems Biomedical Informatics Research Center, Seoul National University, Seoul, Korea.
authors.forename: Young-Ji
authors.initials: YJ
authors.lastname: Na
authors.forename: Yonglae
authors.initials: Y
authors.lastname: Cho
authors.forename: Ju Han
authors.initials: JH
authors.lastname: Kim
keywords: DNA Sequence Analysis; Disease; Genome Structural Variation; High-Throughput Nucleotide Sequencing; Molecular Sequence Annotation