The general workflow outlined in this tutorial is intended to emulate a study, whereby one does a whole genome scan on individual markers and then hones in on significant regions for a more in-depth investigation of LD and haplotypes.
You’ll notice a couple datasets already created in the project including a joined spreadsheet of phenotype and genotype data for the HapMap samples (HapMap Phenotype + 500K Genotypes) as well as an association test results spreadsheet (Association Tests (Genotypic Tests)).
A p-value plot is created. Notice, there are two regions of significance, one on chr14 and the other on chr22. In this tutorial we will focus on the chr22 region.
You should now be zoomed into a region on 22q12.3 covering approximately 35kb (Figure 2a).
You can add an LD plot to an existing graph from any spreadsheet that contains column marker mapped genotype data. In this case you want to generate an LD plot from the same genotype spreadsheet used to produce the association test results.
Under the Add Graph tab, you’ll notice that the same spreadsheet used to create the initial p-value plot is selected by default with corresponding options of graphs you can add based on the spreadsheet selected. You want to change this spreadsheet to HapMap Phenotype + 500K Genotypes.
An LD plot will now appear under the p-value plot and an LD node (HapMap Phenotype + 500K Genotypes) will appear in the Graph Control Interface along with its associated Haplotype Block Set graph item (Figure 2b).
Notice the apparent block of LD (red) in the middle of the plot interrupted by a single SNP that is uncorrelated (blue) with the other markers.