RegionalP: A region-based meta-analysis of genome-wide association studies in genetically diverse populations
This C++ program works by quantifying the degree of over-representation of associated SNPs in a pre-defined genomic region, given a specific definition of statistical significance. For example, under the null hypothesis that the region is independent of the phenotype, we expect 5% of the SNPs to be statistically significant by chance when adopting a P-value threshold of 5%, giving all the SNPs in this region are mutually independent. An over-representation of statistically significant SNPs in this region constitutes evidence that this region is associated with the phenotype, with the extent of over-representation indicating the strength of the evidence. The effective number of independent SNPs and the number of independent SNPs exhibiting evidence of phenotypic association is evaluated using Eigen-decomposition of the matrix measuring the LD between every possible pair of SNPs in the region.
This region-based analysis can be generalized to perform gene-based or pathway-based analyses.
We have just released the updated software with minor bugs fixed and new versions for different platforms, referred as RegionalP [Beta-version]. The original software is referred to as [Alpha-version]. The format for the input and output files do not change.
- RegionalP [Alpha-version] A zipped file containing the software can be downloaded. Please refer to the README.region for program instructions.
- RegionalP-Beta_MAC.zip For Mac OSX Intel
- RegionalP-Beta_Linux.zip For Linux (x86_64) Executable
The following zipped file contains example datasets for regionalP.
Please cite the following publication if you are using the program in any publication.
- X.Wang et al. :A statistical method for region-based meta-analysis of genome-wide association studies in genetically diverse population (submitted)
If you have any questions regarding the use of the program, please send an e-mail to both of the following people:
- Wang Xu ( email@example.com )
- Dr. Yik Ying Teo ( firstname.lastname@example.org )