Hi,
I have found ~ 200 significant associations at a specific p-value threshold by running a GWAS between SNPs and a phenotype. I can map the significant SNPs to human genes, but I would like to find the independent signals associated with the phenotype, i.e. if the genes where the SNPs map to are nearby and there is LD between these genes, then I would like to consider the associations as a unique signal. I think this is a normal step to find the independent signals in post-GWAS processing.
My question is, is there a way to do this in R or any software, so retrieving the LD between a list of SNPs (something like BiomaRt) and then using this information to find independent signals, maybe creating LD clusters? I don't know if this is the usual way of finding independent signals in a GWAS, if not, could you tell me how this is normally done?
Thank you for any advice/help/suggestion!
EDIT by Michael: This boils down to the question if there is a tool like SNAP but for local installation.
What do you mean by "consider as a unique signal", do you mean to consider them jointly or giving them a compound score? I wouldn't call that independent, because they are in LD, it is quite the opposite.
Hi Micael, thanks for your reply. No I don't want a score, just the genes/signals found in thie GWAS that are independent, so for ex. if SNP1 maps to gene1 and SNP2 maps to genes2, but gene1 and gene2 are in LD, then there will be only one signal from this region… Isn't this how usually the number of independent associated loci are found?
Ok, I think I understand now. So, you wish to find if significant markers are in LD with each other given a cut-off for r2? LD is only measured for markers not for genes.
that is not an answer i think this paper may help
Investigation of a genome wide association signal for obesity: synthetic association and haplotype analyses at the melanocortin 4 receptor gene locus.