SNVerGUI: A desktop tool for variant analysis of next-generation sequencing data

Document Type

Article

Publication Date

12-1-2012

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. Method and 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.

Identifier

84872036861 (Scopus)

Publication Title

Journal of Medical Genetics

External Full Text Location

https://doi.org/10.1136/jmedgenet-2012-101001

e-ISSN

14686244

ISSN

00222593

PubMed ID

23024288

First Page

753

Last Page

755

Issue

12

Volume

49

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