Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
Nucleic Acids Res. 2012 Jan;40(Database issue):D1036-40. doi: 10.1093/nar/gkr899. Epub 2011 Nov 3.
Genome-wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with the risk of hundreds of diseases. However, there is currently no database that enables non-specialists to answer the following simple questions: which SNPs associated with diseases are in linkage disequilibrium (LD) with a gene of interest? Which chromosomal regions have been associated with a given disease, and which are the potentially causal genes in each region? To answer these questions, we use data from the HapMap Project to partition each chromosome into so-called LD blocks, so that SNPs in LD with each other are preferentially in the same block, whereas SNPs not in LD are in different blocks. By projecting SNPs and genes onto LD blocks, the DistiLD database aims to increase usage of existing GWAS results by making it easy to query and visualize disease-associated SNPs and genes in their chromosomal context. The database is available at http://distild.jensenlab.org/.
全基因组关联研究 (GWAS) 已经确定了数千个与数百种疾病风险相关的单核苷酸多态性 (SNP)。然而，目前还没有一个数据库可以让非专业人士回答以下简单的问题：与疾病相关的哪些 SNP 与感兴趣的基因呈连锁不平衡 (LD)？哪些染色体区域与特定疾病相关，每个区域的潜在因果基因是什么？为了回答这些问题，我们使用 HapMap 项目的数据将每条染色体划分为所谓的 LD 块，以便彼此呈 LD 的 SNP 优先位于同一块中，而不呈 LD 的 SNP 位于不同的块中。通过将 SNPs 和基因映射到 LD 块上，DistiLD 数据库旨在通过使其易于查询和可视化染色体背景下与疾病相关的 SNPs 和基因，来增加对现有 GWAS 结果的使用。该数据库可在 http://distild.jensenlab.org/ 获得。
