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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Related Experiment Video

Updated: May 20, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Published on: December 7, 2021

HapZipper: sharing HapMap populations just got easier.

Pritam Chanda1, Eran Elhaik, Joel S Bader

  • 1Department of Biomedical Engineering, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, McKusick-Nathans Institute of Genetic Medicine, Baltimore, MD 21205, USA.

Nucleic Acids Research
|July 31, 2012
PubMed
Summary
This summary is machine-generated.

Genomic data storage is challenging. HapZipper, a new lossless compression tool, significantly reduces HapMap data size, outperforming generic methods for efficient genetic data archiving and analysis.

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Last Updated: May 20, 2026

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Published on: May 6, 2010

Area of Science:

  • Genomics
  • Bioinformatics
  • Data Science

Background:

  • The exponential growth of genomic sequence data presents significant storage and network challenges.
  • Existing generic compression tools are insufficient for the unique characteristics of large-scale genetic datasets.
  • Efficient data archiving and analysis are crucial for genomics research.

Purpose of the Study:

  • To develop an advanced data compression technique specifically for genetic data.
  • To introduce HapZipper, a novel lossless compression tool tailored for HapMap data.
  • To demonstrate the superior performance of HapZipper compared to generic compression methods.

Main Methods:

  • HapZipper was developed as a specialized lossless compression tool.
  • The tool was designed to leverage the standard format and biological properties of HapMap data.
  • Performance was benchmarked against generic compression tools like gzip, bzip2, and lzma.

Main Results:

  • HapZipper achieved significant compression ratios for HapMap data.
  • HapMap 3 populations were compressed to less than 5% of their original size.
  • HapZipper outperformed established generic compression tools in compressing genetic data.

Conclusions:

  • HapZipper offers a highly effective solution for compressing large-scale genetic datasets.
  • The specialized approach significantly improves data storage and archiving efficiency.
  • HapZipper is a valuable tool for the genomics community, facilitating data management and analysis.