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Forer, L.* ; Schönherr, S.* ; Weissensteiner, H.* ; Haider, F.* ; Kluckner, T.* ; Gieger, C. ; Wichmann, H.-E. ; Specht, G.* ; Kronenberg, F.* ; Kloss-Brandstätter, A.*

CONAN: Copy number variation analysis software for genome-wide association studies.

BMC Bioinformatics 11:318 (2010)
Verlagsversion Volltext DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
BACKGROUND: Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs. RESULTS: CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data. CONCLUSIONS: CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at http://genepi-conan.i-med.ac.at.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter HIDDEN-MARKOV MODEL; SNP GENOTYPING DATA; POPULATION; ECOMPAGT
Sprache englisch
Veröffentlichungsjahr 2010
HGF-Berichtsjahr 2010
ISSN (print) / ISBN 1471-2105
e-ISSN 1471-2105
Zeitschrift BMC Bioinformatics
Quellenangaben Band: 11, Heft: , Seiten: , Artikelnummer: 318 Supplement: ,
Verlag BioMed Central
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Epidemiology (EPI)
POF Topic(s) 30503 - Chronic Diseases of the Lung and Allergies
Forschungsfeld(er) Genetics and Epidemiology
PSP-Element(e) G-503900-001
PubMed ID 20546565
Scopus ID 77953344765
Erfassungsdatum 2010-09-09