Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/86846
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Type: Journal article
Title: SimHap GUI: an intuitive graphical user interface for genetic association analysis
Author: Carter, K.
McCaskie, P.
Palmer, L.
Citation: BMC Bioinformatics, 2008; 9(1):557-1-557-6
Publisher: BioMed Central
Issue Date: 2008
ISSN: 1471-2105
1471-2105
Statement of
Responsibility: 
Kim W Carter, Pamela A McCaskie, Lyle J Palmer
Abstract: Background: Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool. Results: We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress. Conclusion: SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.
Keywords: Haplotypes; Polymorphism, Single Nucleotide; Algorithms; Computer Graphics; Software; Programming Languages; User-Computer Interface; Genome-Wide Association Study
Rights: © 2008 Carter et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
RMID: 0020136656
DOI: 10.1186/1471-2105-9-557
Appears in Collections:Translational Health Science publications

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