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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
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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,...
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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Related Experiment Video

Updated: Nov 12, 2025

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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LocusZoom.js: interactive and embeddable visualization of genetic association study results.

Andrew P Boughton1, Ryan P Welch1, Matthew Flickinger1

  • 1Department of Biostatistics and the Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA.

Bioinformatics (Oxford, England)
|March 18, 2021
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Summary

LocusZoom.js is an open-source JavaScript library for interactive visualization of genetic association study results. It enables exploration of genomic data, gene models, and other annotations, facilitating variant analysis and data sharing.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genetic association studies generate large datasets requiring effective visualization tools.
  • Interpreting complex genomic data and identifying causal variants is a significant challenge.

Purpose of the Study:

  • To introduce LocusZoom.js, a JavaScript library for creating interactive web-based visualizations of genetic association study results.
  • To provide a flexible tool for exploring genomic data, annotations, and refining analysis models.

Main Methods:

  • Development of a JavaScript library (LocusZoom.js) for genetic data visualization.
  • Integration of features for displaying genetic association results alongside gene models and genomic annotations.
  • Implementation of interactive functionalities for refining analysis models, including linkage disequilibrium selection and causal variant identification.

Main Results:

  • LocusZoom.js enables interactive visualization of genetic association results and related genomic data.
  • The library supports customization for various data types, including PheWAS, chromatin co-accessibility, and eQTL data.
  • A new web upload service simplifies data harmonization, annotation, and exploration of user-provided results.

Conclusions:

  • LocusZoom.js offers a powerful and flexible platform for visualizing and exploring genetic association study results.
  • The open-source nature and web-based accessibility promote data sharing and collaborative research in genomics.