The advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations.
To facilitate analysis of HapMap data for characterizing the haplotype structure of genes or any chromosomal regions, we have developed an integrated web-based resource, iHAP. In addition to incorporating genotype and haplotype data from the International HapMap Project and gene information from the UCSC Genome Browser Database, iHAP also provides capabilities for inferring haplotype blocks and selecting tag SNPs that are representative of haplotype patterns. These include block partitioning algorithms, block definitions, tag SNP definitions, as well as SNPs to be "force included" as tags. Based on the parameters defined at the input stage, iHAP performs on-the-fly analysis and displays the result graphically as a webpage. To facilitate analysis, intermediate and final result files can be downloaded.
The iHAP resource, available at http://ihap.bii.a-star.edu.sg webcite, provides a convenient yet flexible approach for the user community to analyze HapMap data and identify candidate targets for genotyping studies.
