共 19 条
GENOMIZER:: An integrated analysis system for genome-wide association data
被引:20
作者:
Franke, Andre
Wollstein, Andreas
Teuber, Markus
Wittig, Michael
Lu, Tim
Hoffmann, Katrin
Nuernberg, Peter
Krawczak, Michael
Schreiber, Stefan
Hampe, Jochen
机构:
[1] Univ Kiel, Kiel Ctr German Natl Genotyping Platform, Inst Clin Mol Biol, D-24105 Kiel, Germany
[2] Univ Kiel, Inst Med Informat & Stat, D-24105 Kiel, Germany
[3] Univ Kiel, Dept Med 1, D-24105 Kiel, Germany
[4] Charite Univ Hosp, Dept Human Genet, Berlin, Germany
[5] Univ Cologne, Cologne Ctr Genom, Cologne, Germany
关键词:
genome-wide association;
complex disease;
software;
D O I:
10.1002/humu.20306
中图分类号:
Q3 [遗传学];
学科分类号:
071007 ;
090102 ;
摘要:
Genome-wide association analysis appears to be a promising way to identify heritable susceptibility factors for complex human disorders. However, the feasibility of large-scale genotyping experiments is currently limited by an incomplete marker coverage of the genome, a restricted understanding of the functional role of given genomic regions, and the small sample sizes used. Thus, genome-wide association analysis will be a screening tool to facilitate subsequent gene discovery rather than a means to completely resolve individual genetic risk profiles. The validation of association findings will continue to rely upon the replication of "leads" in independent samples from either the same or different populations. Even under such pragmatic conditions, the timely analysis of the large data sets in question poses serious technical challenges. We have therefore developed public,domain software, GENOMIZER, that implements the workflow of an association experiment, including data management, single-point and haplotype analysis, "lead" definition, and data visualization. GENOMIZER (www.ikmb.uni-kiel.de/genomizer) comes with a complete user manual, and is open source software licensed under the GNU Lesser General Public License. We suggest that the use of this software facilitate the handling and interpretation of the currently emerging genome-wide association data.
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页码:583 / 588
页数:6
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