Exploiting large scale computing to construct high resolution linkage disequilibrium maps of the human genome

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Linkage disequilibrium (LD) maps are crucial for association mapping, marker spacing optimization, and identifying regions under natural selection.
• HapMap phase II offers significantly more single nucleotide polymorphisms (SNPs) than phase I, enabling the creation of higher-resolution LD maps.

Purpose of the Study:

• To construct high-resolution, genome-wide linkage disequilibrium (LD) maps.
• To leverage the increased SNP density from HapMap phase II data.
• To introduce and utilize the LDMAP-cluster program for efficient map construction.

Main Methods:

• Employed the LDMAP-cluster parallel program in a Linux environment.
• Utilized a dataset comprising over 8.2 million SNPs from the HapMap phase II data.
• Constructed genome-wide LD maps.

Main Results:

• Successfully generated comprehensive genome-wide LD maps.
• The maps are of higher resolution due to the increased number of SNPs from HapMap phase II.
• The LDMAP-cluster program facilitated rapid map construction.

Conclusions:

• LDMAP-cluster is an effective tool for rapid construction of high-resolution LD maps.
• The generated LD maps are valuable resources for various genetic analyses, including association mapping and evolutionary studies.
• The increased SNP density in HapMap phase II significantly enhances the utility of LD mapping.