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.
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.
Authors: W James Kent; Charles W Sugnet; Terrence S Furey; Krishna M Roskin; Tom H Pringle; Alan M Zahler; David Haussler Journal: Genome Res Date: 2002-06 Impact factor: 9.043
Authors: Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham Journal: Am J Hum Genet Date: 2007-07-25 Impact factor: 11.025
Authors: Lucia A Hindorff; Praveen Sethupathy; Heather A Junkins; Erin M Ramos; Jayashri P Mehta; Francis S Collins; Teri A Manolio Journal: Proc Natl Acad Sci U S A Date: 2009-05-27 Impact factor: 11.205
Authors: David A Wheeler; Maithreyan Srinivasan; Michael Egholm; Yufeng Shen; Lei Chen; Amy McGuire; Wen He; Yi-Ju Chen; Vinod Makhijani; G Thomas Roth; Xavier Gomes; Karrie Tartaro; Faheem Niazi; Cynthia L Turcotte; Gerard P Irzyk; James R Lupski; Craig Chinault; Xing-zhi Song; Yue Liu; Ye Yuan; Lynne Nazareth; Xiang Qin; Donna M Muzny; Marcel Margulies; George M Weinstock; Richard A Gibbs; Jonathan M Rothberg Journal: Nature Date: 2008-04-17 Impact factor: 49.962
Authors: Kai Wang; Mingyao Li; Dexter Hadley; Rui Liu; Joseph Glessner; Struan F A Grant; Hakon Hakonarson; Maja Bucan Journal: Genome Res Date: 2007-10-05 Impact factor: 9.043
Authors: Richard Redon; Shumpei Ishikawa; Karen R Fitch; Lars Feuk; George H Perry; T Daniel Andrews; Heike Fiegler; Michael H Shapero; Andrew R Carson; Wenwei Chen; Eun Kyung Cho; Stephanie Dallaire; Jennifer L Freeman; Juan R González; Mònica Gratacòs; Jing Huang; Dimitrios Kalaitzopoulos; Daisuke Komura; Jeffrey R MacDonald; Christian R Marshall; Rui Mei; Lyndal Montgomery; Kunihiro Nishimura; Kohji Okamura; Fan Shen; Martin J Somerville; Joelle Tchinda; Armand Valsesia; Cara Woodwark; Fengtang Yang; Junjun Zhang; Tatiana Zerjal; Jane Zhang; Lluis Armengol; Donald F Conrad; Xavier Estivill; Chris Tyler-Smith; Nigel P Carter; Hiroyuki Aburatani; Charles Lee; Keith W Jones; Stephen W Scherer; Matthew E Hurles Journal: Nature Date: 2006-11-23 Impact factor: 49.962
Authors: Edward J Hollox; Ulrike Huffmeier; Patrick L J M Zeeuwen; Raquel Palla; Jesús Lascorz; Diana Rodijk-Olthuis; Peter C M van de Kerkhof; Heiko Traupe; Gys de Jongh; Martin den Heijer; André Reis; John A L Armour; Joost Schalkwijk Journal: Nat Genet Date: 2007-12-02 Impact factor: 38.330
Authors: Stefano Colella; Christopher Yau; Jennifer M Taylor; Ghazala Mirza; Helen Butler; Penny Clouston; Anne S Bassett; Anneke Seller; Christopher C Holmes; Jiannis Ragoussis Journal: Nucleic Acids Res Date: 2007-03-06 Impact factor: 16.971
Authors: P Flicek; B L Aken; K Beal; B Ballester; M Caccamo; Y Chen; L Clarke; G Coates; F Cunningham; T Cutts; T Down; S C Dyer; T Eyre; S Fitzgerald; J Fernandez-Banet; S Gräf; S Haider; M Hammond; R Holland; K L Howe; K Howe; N Johnson; A Jenkinson; A Kähäri; D Keefe; F Kokocinski; E Kulesha; D Lawson; I Longden; K Megy; P Meidl; B Overduin; A Parker; B Pritchard; A Prlic; S Rice; D Rios; M Schuster; I Sealy; G Slater; D Smedley; G Spudich; S Trevanion; A J Vilella; J Vogel; S White; M Wood; E Birney; T Cox; V Curwen; R Durbin; X M Fernandez-Suarez; J Herrero; T J P Hubbard; A Kasprzyk; G Proctor; J Smith; A Ureta-Vidal; S Searle Journal: Nucleic Acids Res Date: 2007-11-13 Impact factor: 16.971
Authors: Benjamin L Kidder; Runsheng He; Darawalee Wangsa; Hesed M Padilla-Nash; M Margarida Bernardo; Shijie Sheng; Thomas Ried; Keji Zhao Journal: Cancer Res Date: 2017-09-26 Impact factor: 12.701
Authors: Robert Makowsky; Nicholas M Pajewski; Yann C Klimentidis; Ana I Vazquez; Christine W Duarte; David B Allison; Gustavo de los Campos Journal: PLoS Genet Date: 2011-04-28 Impact factor: 5.917
Authors: Ian M Carr; Christine P Diggle; Kamron Khan; Chris Inglehearn; Martin McKibbin; David T Bonthron; Alexander F Markham; Rashida Anwar; Angus Dobbie; Sergio D J Pena; Manir Ali Journal: PLoS One Date: 2012-08-17 Impact factor: 3.240
Authors: Katie E Fowler; Ricardo Pong-Wong; Julien Bauer; Emily J Clemente; Christopher P Reitter; Nabeel A Affara; Stephen Waite; Grant A Walling; Darren K Griffin Journal: BMC Genomics Date: 2013-11-13 Impact factor: 3.969