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. 2012 Nov 1;40(20):e159.
doi: 10.1093/nar/gks709. Epub 2012 Jul 27.

HapZipper: sharing HapMap populations just got easier

Pritam Chanda  1 , Eran Elhaik, Joel S Bader
Affiliations

HapZipper: sharing HapMap populations just got easier

Pritam Chanda et al. Nucleic Acids Res. .

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.

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Figures

Figure 1.
Figure 1.
HapZipper compression diagram provided a dbSNP database. Phased haplotypes are compared with dbSNP SNPs and classified into four categories: EX-SNPs, SF-SNPs, RM-SNPs and N-SNPs that include novel SNPs (Nnew-SNP) and SNPs that are similar to dbSNP except the alleles (Nallele-SNP). Using dbSNP, the haplotype data are encoded into a bit-vector A, which corresponds dbSNP SNPs, and a bit-matrix B, which encodes all the alleles marked as 1 in bit-vector A. The bit-matrix B is then divided into two bit-matrices B1 and B2, based on the MAF of the SNPs. The binary bit-vector Bv represents the bit-matrices order in the original matrix. The information for categorical SNPs is stored in three tables: T-SF, T-RM and T-N that are further compressed using relative positions and varying bits per integer. In the absence of a dbSNP database only the table T-N is used.
Figure 2.
Figure 2.
Storing relative positions using varying number of bits. The binary representation of each relative position (top row) and the corresponding encoded binary value (bottom row) are shown for boundary values 127, 128, 16 383 and 16 384. A bit in black shows the flag bit within an encoded byte that indicates beginning of a relative position value with a 0.
Figure 3.
Figure 3.
A comparison of the compression tool fold-compressions on six HapMap population datasets of various sizes.
Figure 4.
Figure 4.
A comparison of the compression tool total run-time (compression + decompression) using six HapMap population datasets of various sizes.
See this image and copyright information in PMC

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