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QCGWAS / Quality Control of Genome Wide Association Study results

An R package that automates the quality control of genome-wide association result files. Its main purpose is to facilitate the quality control of a large number of such files before meta-analysis. Alternatively, it can be used by individual cohorts to check their own result files. QCGWAS is flexible and has a wide range of options, allowing rapid generation of high-quality input files for meta-analysis of genome-wide association studies.


Estimates Bayes and local Bayes false discovery rates (FDR) for replicability analysis. Repfdr provides a way of performing analysis and theoretical justifications. This approach is a general method for assessing replicability in several studies when each study examines the same hypotheses. It can be used for applications like genome-wide association studies (GWAS) and other, as long as the marginal and non-null densities can still be reasonably well approximated for each study.


An R/Bioconductor package for quality control and analysis of genome-wide association studies (GWAS). GWASTools brings the interactive capability and extensive statistical libraries of R to GWAS. Data are stored in NetCDF format to accommodate extremely large datasets that cannot fit within R's memory limits. The benefits of GWASTools include the interactive analysis provided by R’s interface and the ability to include intensity data. Intensity data can be used to detect sex chromosome aneuploidies (which can be confused with sex mis-annotation), autosomal anomalies (which generate genotyping errors) and evaluation of clustering by genotype call. The documentation includes instructions for converting data from multiple formats, including variants called from sequencing. GWASTools provides a convenient interface for linking genotypes and intensity data with sample and single nucleotide polymorphism annotation.