Literature DB >> 17400728

Management, presentation and interpretation of genome scans using GSCANDB.

Martin Taylor1, William Valdar, Ashish Kumar, Jonathan Flint, Richard Mott.   

Abstract

MOTIVATION: Advances in high-throughput genotyping have made it possible to carry out genome-wide association studies using very high densities of genetic markers. This has led to the problem of the storage, management, quality control, presentation and interpretation of results. In order to achieve a successful outcome, it may be necessary to analyse the data in different ways and compare the results with genome annotations and other genome scans.
RESULTS: We created GSCANDB, a database for genome scan data, using a MySQL backend and Perl-CGI web interface. It displays genome scans of multiple phenotypes analysed in different ways and projected onto genome annotations derived from EnsMart. The current version is optimized for analysis of mouse data, but is customizable to other species. AVAILABILITY: Source code and example data are available under the GPL, in versions tailored to either human or mouse association studies, from http://gscan.well.ox.ac.uk/software.

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Mesh:

Year:  2007        PMID: 17400728     DOI: 10.1093/bioinformatics/btm123

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  Genome-wide association studies: quality control and population-based measures.

Authors:  Andreas Ziegler
Journal:  Genet Epidemiol       Date:  2009       Impact factor: 2.135

2.  A Multiparent Advanced Generation Inter-Cross to fine-map quantitative traits in Arabidopsis thaliana.

Authors:  Paula X Kover; William Valdar; Joseph Trakalo; Nora Scarcelli; Ian M Ehrenreich; Michael D Purugganan; Caroline Durrant; Richard Mott
Journal:  PLoS Genet       Date:  2009-07-10       Impact factor: 5.917

3.  Toppar: an interactive browser for viewing association study results.

Authors:  Thorhildur Juliusdottir; Karina Banasik; Neil R Robertson; Richard Mott; Mark I McCarthy
Journal:  Bioinformatics       Date:  2018-06-01       Impact factor: 6.937

  3 in total

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