The gwama genomewide association meta analysis software has been developed to perform meta analysis of summary statistics generated from genomewide association studies of dichotomous. Meta analysis is a powerful tool to cumulate and summarize the knowledge in a. Kwon3d kwon3d was born in 1990 as a lowend, yet powerful, comprehensive motion analysis software. Meta analysis results in little or no loss of efficiency compared to analysis of a combined dataset including data from all individual studies. Gwama genomewide association meta analysis software has been developed to perform meta analysis of the results of gwa studies of binary or quantitative phenotypes. In this section you can download the metaeasy excel addin, described in the journal of statistical software click here for the paper. The gwama genomewide association metaanalysis software has been developed to perform metaanalysis of summary statistics. The metal software is designed to facilitate meta analysis of large datasets such as several whole genome scans in a convenient, rapid and memory efficient. The meta analysis procedures in ncss are easytouse and validated for accuracy. These include fixed and random effects analysis, fixed and mixed effects meta regression, forest and funnel plots, tests for funnel plot asymmetry, trimandfill and failsafe n analysis. Genomewide association metaanalysis identifies potential. Gwama genomewide association meta analysis software to perform meta analysis of the results of gwa studies of binary or quantitative phenotypes. The theory and statistical foundations of metaanalysis continually evolve, providing solutions to many new and challenging problems.
The gwama genomewide association metaanalysis software has been developed to perform meta analysis of summary statistics generated from genome. In genetics, a genomewide association study gwa study, or gwas, also known as whole genome association study wga study, or wgas, is an observational study of a genomewide set of genetic. Results we have developed flexible, opensource software for the meta analysis. The meta analytic community has contributed to this growth by developing numerous packages specific to meta analysis. Metaanalysis of genomewide association studies and. Forestpmplot is a free, opensource a pythoninterfaced r package tool for analyzing the heterogeneous studies in meta analysis by visualizing the. The gwama genomewide association metaanalysis software has been developed to perform meta analysis of summary statistics generated from genomewide association studies of dichotomous. The r package easystrata facilitates the evaluation and visualization of stratified genomewide association meta analyses gwamas results.
I am performing a meta analysis of multiple gwas data and now, after an intensive qc, i have to choose a suitable software for doing it. Genomewide association metaanalysis of 78,308 individuals identifies new loci and genes influencing human intelligence suzanne sniekers1, sven stringer1, kyoko watanabe1, philip r jansen1,2. Gwama genomewide association meta analysis software performs meta analysis of the results of gwa studies of binary or quantitative. Most of the meta analysis software packages discussed above have varying bioinformatics features to resolve this problem, including metal, metabel, meta. Scott parrott, phd, department of interdisciplinary studies, rutgers university.
Metaanalysis using genomewide association metaanalysis. Metaanalysis using genomewide association metaanalysis gwama tool. Fixed and randomeffect meta analyses are performed for both directly genotyped and imputed snps using estimates of the allelic odds ratio and 95% confidence interval for binary traits, and estimates. The purpose of this study is to locate all publicly available meta analytic r packages. One of the most common questions we receive is about the approach used by metal to carry out a meta analysis using pvalues as input. Perform publication bias analysis additional resources. An inverse varianceweighted fixed effects model was used in the meta analysis as implemented in the gwama software v. Metaanalysis method there are three different metaanalysis methods available controlled by the method optionmethod 1. Although statistical software analysis packages incorporate routines for meta analysis, they are ill equipped to meet the challenges of the scale and complexity of data generated in genomewide association studies. Meta analysis of the discovery and replication cohorts was performed using the gwama software and a randomeffect method. The new release of jasp supports an extensive arrange of commonly used techniques for meta analysis. Genomewide association metaanalysis of eight independent. Although much of the heritability remains unexplained, combining single nucleotide polymorphism snp genotypes from multiple studies for meta analysis will increase the statistical power to identify new diseaseassociated variants. I am performing a metaanalysis of multiple gwas data and now, after an intensive qc, i have to choose a suitable software for doing it.
If you load data for additional studies and repeat the meta analysis command, those results will be stored in a file named metaanalysis2. Metasoft is a meta analysis software designed for performing a range of basic and advanced meta analytic methods. For comparison purposes, we need to mention that only plink and gwama offer the option for random effects meta analysis, whereas metabel and metal allow only fixed effect. However, these tools perform only basic sanity checks before meta. However, to gain insights into increasingly more modest signals of association, samples of many thousands of individuals are required. To estimate meta analysis models, the opensource statistical environment r is quickly becoming a popular choice. Let me know in the comment section below what meta analysis software you are using. Genomewide association meta analysis software performs metaanalysis of the results of gwa studies of binary or quantitative phenotypes.
Gwama can be used for analysing the results of all different genetic models multiplicative, additive, dominant, recessive. Furthermore, our approach to evaluate the evidence for heterogeneity of allelic effects between males and females is equivalent to a formal test of interaction with sex. Education software downloads metastat by ericae and many more programs are available for instant and free download. Meta analysis results are stored in the file metaanalysis1. Genomewide association metaanalysis of 1,447,416 markers, applying the additive. Metaanalysis is increasingly used as a key source of evidence synthesis to inform clinical practice. Meta analysis of genomewide association studies gwass has become a popular method for discovering genetic risk variants. Finally, genomewide association metaanalysis of the eight strata was performed using the gwama software. We implemented the meta analysis methodology in an microsoft excel addin which is freely available and incorporates more meta analysis models including the iterative maximum likelihood and profile likelihood than are usually available, while paying particular attention to the userfriendliness of the package. The name mix comes from metaanalysis in excel and 2. Metaanalysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. The gwama genomewide association metaanalysis software has been developed to perform meta analysis of summary statistics generated.
Fixed effects model fe, random effects model re, han and eskins random effects model re2 and binary effects model be. Gwama genomewide association meta analysis software to perform meta analysis. Here, we overview both widely applied and newer statistical methods for. Jul 19, 2014 genomewide association studies gwas have successfully identified genes associated with complex human diseases. Metaanalysis software forest plot radial plot ncss. Introduction to the statistical analysis of genomewide. Hugh watkins, sekar kathiresan, ruth mcpherson, martin farrall and colleagues report the results of a large genomewide association metaanalysis of coronary artery disease based on. Ncss includes tools for performing meta analysis of means, proportions, correlated proportions, and hazard ratios.
I am performing a metaanalysis of multiple gwas data and now, after an intensive qc, i have to choose a. Software tool for meta analysis of whole genome association data background genomewide association gwa studies have proved to be extremely successful in identifying moderate genetic effects contributing to complex human phenotypes. The key advantage of our framework is the basis on meta. Even for the standard meta analysis that assumes a model of inheritance beforehand, gwar is unique since it offers the option for both fixed and random effects meta analysis.
Gwama meta analysis of whole genome association data. You can change default output file names with the outfile command. Gwama genomewide association meta analysis software performs metaanalysis of the results of gwa studies of binary or quantitative. The gwama genomewide association metaanalysis software has been developed to perform meta analysis of summary statistics generated from genomewide association. Performs meta analysis of summary statistics generated from genomewide association studies of dichotomous phenotypes or quantitative traits. Kwon3d kwon3d was born in 1990 as a lowend, yet powerful, comprehensive motion analysis software package. Code for multivariate genome wide association meta analysis. Gwama genomewide association meta analysis software performs meta analysis of the results of gwa studies of binary or quantitative phenotypes. A meta analysis of genomewide association studies gwas of cutaneous melanoma cm and transcriptome association approaches identified 85 genomic loci that influence cm risk. Metaanalysis methods for genomewide association studies.
Software tool for meta analysis of whole genome association data background genomewide association gwa studies have proved to be extremely successful. Meta analysis reference manual, especially introduction to meta analysis introduction to meta meta analysis in stata. In practice, most meta analyses are performed in general statistical packages or dedicated metaanalysis programs. Software tool for meta analysis of whole genome association data background genomewide association gwa studies have proved to be extremely successful in identifying moderate genetic. The gwama genomewide association meta analysis software has been developed to perform meta analysis of summary statistics generated from genome. Combining association summary statistics across gwas using fixedand randomeffects metaanalysis. The gwama genomewide association meta analysis software has been developed to perform meta analysis of summary statistics generated from genomewide association studies of dichotomous phenotypes or quantitative traits. Data visualization can play an important role in research, specifically in data analysis to complement other analysis methods, such as statistical analysis. It has been around for more than 10 years and has been used in hundreds of analyses and publications. From literature it seems that the most used tool is.
One of the most common questions we receive is about the approach used by metal to carry out a meta analysis. If playback doesnt begin shortly, try restarting your device. There are loads of packages in r associated with meta analysis. The gwama genomewide association meta analysis software has been developed to perform meta analysis of summary statistics generated. The gwama genomewide association metaanalysis software has been developed to perform metaanalysis of summary statistics generated from. Performs metaanalysis of summary statistics generated from genomewide association studies. The gwama genomewide association metaanalysis software has been developed to perform meta analysis of summary statistics generated from genomewide association studies of dichotomous phenotypes or quantitative traits.
Use the links below to jump to the meta analysis topic you would like to examine. There are good meta analysis methods available, but even when they are carefully and optimally applied there remain some unresolved statistical issues. The software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genomewide meta analysis results. Metaanalysis methods for genomewide association studies and. Add the meta analysis reportdups flag if you want the later appearances to be logged in the. To estimate metaanalysis models, the opensource statistical. Metaanalysis for families of experiments in software. May 28, 2010 the software is distributed with scripts that allow simple formatting of files containing the results of each association study and generate graphical summaries of genomewide meta analysis results. Results we have developed flexible, opensource software for the meta analysis of genomewide association studies. Thirdly, in 350 individuals of the sfs, rs6918289 was tested for association. Gwama tutorial university of tartu institute of genomics. Thirdly, in 350 individuals of the sfs, rs6918289 was tested for association with imtf. Ten simple rules for carrying out and writing metaanalyses.
Metasoft is a free, opensource meta analysis software tool for genomewide association study analysis, designed to perform a range of basic and advanced meta analytic methods in an efficient manner. The gwama genomewide association metaanalysis software has been developed to perform meta analysis. May 21, 20 among the existing meta analysis software tools, revman 5. The impressive variety of study designs and outcome measures that can be evaluated plus the graphing capabilities are major advantages of this program. Available metaanalysis software, such as metal willer et al. Which is the best tool for metaanalysis of gwas data. Introduction gwama genomewide association meta analysis software has been developed to perform meta analysis of the results of gwa studies of binary or quantitative phenotypes. We attempted to reproduce the reported meta analysis results using the descriptive statistics and also investigated the validity of the meta analysis. Bonferroni correction was applied in order to adjust for multiple te.