SequenceVariantAnalyzer

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SequenceVariantAnalyzer (SVA) is a computer program for annotating and analyzing genetic variants called (identified) from a whole genome or exome sequencing study (Shotgun sequencing).

Introduction[edit]

Background[edit]

DNA sequence information underpins genetic research, enabling discoversies of important biological or medical benefit.[1] Compared with previous discovery strategies, a whole-genome sequencing study is no longer constrained by differing patterns of linkage disequilibrium,[2] thus, in theory, is more possible to directly identify the genetic variants contributing to biological traits or medical outcomes.

The rapidly evolving high-throughput DNA sequencing technologies have now allowed the fast generation of large amount of sequence data for the purpose of performing such whole-genome sequencing studies, at a reasonable cost. SequenceVariantAnalyzer, or SVA, is a software tool to analyze the genetic variants identified from such studies.

Functions[edit]

SVA is designed for two specific aims:

(1) To annotate the biological functions of the identified genetic variants and group them, conveniently;

(2) To find the genetic variants that are associated with or responsible for the biological traits or medical outcomes of interest.

Language[edit]

SVA is developed on the Java platform.

Authors[edit]

SVA is developed and maintained by Dr. Dongliang Ge and Dr. David B. Goldstein at Duke University, Center for Human Genome Variation.

References[edit]

  1. ^ Bentley DR, Balasubramanian S, Swerdlow HP, et al. (2008). "Accurate whole human genome sequencing using reversible terminator chemistry.". Nature. 456 (7218): 53–59. PMC 2581791Freely accessible. PMID 18987734. doi:10.1038/nature07517. 
  2. ^ Need AC, Goldstein DB (2009). "Next generation disparities in human genomics: concerns and remedies.". Trends in Genetics. 25: 489–494. PMID 19836853. doi:10.1016/j.tig.2009.09.012. 

External links[edit]