Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Highly Accessed Software

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

Lukas Forer1, Sebastian Schönherr12, Hansi Weissensteiner1, Florian Haider1, Thomas Kluckner1, Christian Gieger3, Heinz-Erich Wichmann345, Günther Specht2, Florian Kronenberg1 and Anita Kloss-Brandstätter1*

Author Affiliations

1 Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, 6020 Innsbruck, Austria

2 Department of Database and Information Systems, Institute of Computer Science, University of Innsbruck, 6020 Innsbruck, Austria

3 Institute of Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany

4 Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, 80539 Munich, Germany

5 Klinikum Großhadern, 80337 Munich, Germany

For all author emails, please log on.

BMC Bioinformatics 2010, 11:318  doi:10.1186/1471-2105-11-318

Published: 14 June 2010

Abstract

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 webcite.