catmap: Case-control And TDT Meta-Analysis Package

BackgroundRisk for complex disease is thought to be controlled by multiple genetic risk factors, each with small individual effects. Meta-analyses of several independent studies may be helpful to increase the ability to detect association when effect sizes are modest. Although many software options are available for meta-analysis of genetic case-control data, no currently available software implements the method described by Kazeem and Farrall (2005), which combines data from independent family-based and case-control studies.ResultsI introduce the package catmap for the R statistical computing environment that implements fixed- and random-effects pooled estimates for case-control and transmission disequilibrium methods, allowing for the use of genetic association data across study types. In addition, catmap may be used to create forest and funnel plots and to perform sensitivity analysis and cumulative meta-analysis. catmap is available from the Comprehensive R Archive Network http://www.r-project.org.Conclusioncatmap allows researchers to synthesize data to assess evidence for association in studies of genetic polymorphisms, facilitating the use of pooled data analyses which may increase power to detect moderate genetic associations.

[1]  J. Ioannidis,et al.  Establishment of genetic associations for complex diseases is independent of early study findings , 2004, European Journal of Human Genetics.

[2]  M Farrall,et al.  Integrating case-control and TDT studies. , 2005, Annals of human genetics.

[3]  N. Laird,et al.  Meta-analysis in clinical trials. , 1986, Controlled clinical trials.

[4]  Peter Teunis,et al.  Combining the transmission disequilibrium test and case–control methodology using generalized logistic regression , 2004, European Journal of Human Genetics.

[5]  Chun Li,et al.  Genetic association analysis using data from triads and unrelated subjects. , 2005, American journal of human genetics.

[6]  Nicola J. Camp,et al.  PedGenie: meta genetic association testing in mixed family and case-control designs , 2007, BMC Bioinformatics.

[7]  Douglas G. Altman,et al.  Systematic Reviews in Health Care , 2001 .

[8]  Michael Knapp,et al.  Maximum‐likelihood estimation of haplotype frequencies in nuclear families , 2004, Genetic epidemiology.

[9]  J. Ioannidis,et al.  Replication validity of genetic association studies , 2001, Nature Genetics.

[10]  Douglas G. Altman,et al.  Systematic Reviews in Health Care: Meta-Analysis in Context: Second Edition , 2008 .

[11]  D J Schaid,et al.  Use of parents, sibs, and unrelated controls for detection of associations between genetic markers and disease. , 1998, American journal of human genetics.

[12]  Michael Knapp,et al.  Impact of Missing Genotype Data on Monte-Carlo Simulation Based Haplotype Analysis , 2005, Human Heredity.

[13]  Nicola J. Camp,et al.  PedGenie: an analysis approach for genetic association testing in extended pedigrees and genealogies of arbitrary size , 2006, BMC Bioinformatics.

[14]  M. Farrall,et al.  Integrating Case‐control and TDT Studies , 2005 .