I am fairly new and inexperienced regarding SNP analysis and I am struggling to grasp some details regarding the analysis of association between SNP and clinical data.
At the moment I have a dataset of Whole Exome Sequencing of patients with Alzheimer's disease with their associated clinical data. All patients are not relative and we do not have information regarding the pedigree and family history. I have called the variants with GATK, annotated them with annovar and did some selection based on different annotation parameters. This gave us a small list of candidates to validate.
Now I am asked if I can find groups of SNPs that associates with specific clinical data of the patients. The rationale behind the request is to find, within the population, groups of SNPs that can positively or negatively affect parameters such as memory loss because they consistently associate with individuals with high/low scores of the parameter.
My review of literature and tutorials of the last few days suggest I should go with either GWAS or QTL mapping. It appears however that: 1) GWAS requires matched controls, which we do not have 2) QTL mapping requires more of a map of markers equally spread throughout the genome, rather than only the full list of SNPs.
I came across this post, but I'm not sure which function of PLINK they refer to and if it is exactly what I am looking for. I am now learning the suggested software "MERLIN", but I was wondering what is the golden standard for this kind of analysis (if there is one) or what software you use.