HapZipper: sharing HapMap populations just got easier.

ABSTRACT: The rapidly growing amount of genomic sequence data being generated and made publicly available necessitate the development of new data storage and archiving methods. The vast amount of data being shared and manipulated also create new challenges for network resources. Thus, developing advanced data compression techniques is becoming an integral part of data production and analysis. The HapMap project is one of the largest public resources of human single-nucleotide polymorphisms (SNPs), characterizing over 3 million SNPs genotyped in over 1000 individuals. The standard format and biological properties of HapMap data suggest that a dedicated genetic compression method can outperform generic compression tools. We propose a compression methodology for genetic data by introducing HapZipper, a

SUBMITTER: Chanda P 

PROVIDER: S-EPMC3488212 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature