The DistiLD database aims to increase the usage of existing genome-wide association studies (GWAS) results by making it easy to query and visualize disease-associated SNPs and genes in their chromosomal context. The database performs three important tasks:

  1. published GWAS are collected from several sources and linked to standardized, international disease codes ICD10 codes)
  2. data from the International HapMap Project are analyzed to define linkage disequilibrium (LD) blocks onto which SNPs and genes are mapped
  3. the web interface makes it easy to query and visualize disease-associated SNPs and genes within LD blocks.

Users can query the database by diseases, SNPs or genes. No matter which of the three query modes was used, an intermediate page will be shown listing all the studies that matched the search with a link to the corresponding publication. The user can select either all studies related to a certain disease or one specific study for which to view the related LD blocks.

In the example that we show, we queried the database with the following genes: IKZF1, ARID5B and CEBPE and we see that all three are related to C91.0 - Lymphoid leukemia. When querying the database by SNPs or genes the user can see them highlighted in red. In our example each queried gene maps to a different LD block. We rank the blocks by the p-value of the most statistically significant SNP within each block.

The blocks are represented in boxes where the chromosome is a thin bar in the middle showing the position and orientation of the genes. The genes and intergenic regions are not shown to scale. This schematic view enables the users to visualize large chromosomal regions in a much more compact way than the traditional genome browsers. The SNPs are pointing to their chromosome position by thin lines. To keep a clear view of the blocks, within regions where there is a high density of SNPs we collapse them and we show the number of SNPs collapsed and the best p-value among them.

On clicking the SNPs a popup appears showing all of them and the corresponding publication and p-values associated to them.

It is also possible to obtain information of the protein encoded by the gene on clicking it, using the Reflect web service.

DistiLD is maintained by the Disease Systems Biology Group at the Novo Nordisk Foundation Center for Protein Research at the Faculty of Health Sciences, University of Copenhagen