title: SNVerGUI: a desktop tool for variant analysis of next-generation sequencing data.
abstract: BACKGROUND
  Advances in next generation sequencing (NGS) technology have made it possible to interrogate comprehensively genome-wide genetic variations. However, most existing tools for variation detection are based on command-line interface, which discourages the main end users of NGS data, such as biologists, geneticists and clinicians, from utilising the software.
  
  
  RESULTS
  We have developed the SNVerGUI, a graphical user interface (GUI) based tool for variant detection and analysis. Compared with other methods for variant calling, our approach is unique in that it is applicable to both individual and pooled sequencing data. With friendly GUI, end users can easily adjust running parameters to optimise variant calling for their specific needs. SNVerGUI supports commonly used input and output file formats that allows SNVerGUI to be seamlessly integrated into common NGS data analysis pipelines. SNVerGUI is implemented in Java, which is platform-independent and therefore easy to install and run on the commonly used operating systems, such as Linux, Mac, and Windows. Using two real datasets, we have shown that SNVerGUI is capable of analysing very high volume NGS data in a feasible time on personal computers.
  
  
  CONCLUSIONS
  SNVerGUI is a fast and easy desktop GUI tool for the identification of genomic variants from pooled sequencing and individual sequencing data. Using this software, users can perform sophisticated variant detection by simply configuring several parameters in a friendly graphical user interface. SNVerGUI makes variant analysis as simple and effortless as possible, and we expect it to become popular among geneticists, clinicians, and biologists. SNVerGUI can be freely downloaded from http://snver.sourceforge.net/snvergui/, and will be continuously updated upon users' feedback.
authors.affiliation: Department of Computer Science, New Jersey Institute of Technology, GITC 4400, Newark, NJ 07102, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.forename: Weicheng
authors.initials: W
authors.lastname: Hu
authors.forename: Fang
authors.initials: F
authors.lastname: Hou
authors.forename: Pingzhao
authors.initials: P
authors.lastname: Hu
authors.forename: Zhi
authors.initials: Z
authors.lastname: Wei
mesh_terms: D001289:Attention Deficit Disorder with Hyperactivity / Q000235:genetics; D019295:Computational Biology / Q000379:methods; D057225:Data Mining; D003922:Diabetes Mellitus, Type 1 / Q000235:genetics; D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D017422:Sequence Analysis, DNA; D012984:Software; D014584:User-Computer Interface