HapZipper: sharing HapMap populations just got easier

Research output: Contribution to journalArticle

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 lossless compression tool tailored to compress HapMap data beyond benchmarks defined by generic tools such as gzip, bzip2 and lzma. We demonstrate the usefulness of HapZipper by compressing HapMap 3 populations to <5% of their original sizes. HapZipper is freely downloadable from https://bitbucket.org/pchanda/hapzipper/downloads/HapZipper.tar.bz2.

Details

Authors
External organisations
  • Johns Hopkins University
Research areas and keywords

Keywords

  • Data Compression, HapMap Project, Humans, Polymorphism, Single Nucleotide, Software
Original languageEnglish
Article numbere159
Number of pages7
JournalNucleic Acids Research
Volume40
Issue number20
Publication statusPublished - 2012 Nov 1
Publication categoryResearch
Peer-reviewedYes
Externally publishedYes