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GenPop-An Online Tool to Analyze Human Population Genetic Data.

B Arundhati Mahesh1, E Kannan2, G Dicky John Davis1

  • 1Department of Bioinformatics, Sri Ramachandra Institute of Higher Education and Research (DU), Porur, Chennai ,Tamilnadu, India- 600116.

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|May 15, 2020
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Summary

GenPop is a new web-based tool for analyzing human population genetic data in association studies. It aids geneticists and epidemiologists with various statistical tests and analyses for genetic markers.

Keywords:
GeneticistHardy-Weinberg equilibriumPHPepidemiologist

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Area of Science:

  • Population Genetics
  • Genetic Epidemiology
  • Bioinformatics

Background:

  • Association studies are crucial for understanding human genetic variation and disease.
  • Analyzing large population genetic datasets requires specialized computational tools.
  • Existing tools may lack comprehensive features for complex genetic analyses.

Purpose of the Study:

  • To introduce GenPop, a novel web-based tool for analyzing human population genetic data.
  • To provide geneticists and epidemiologists with a user-friendly platform for association studies.
  • To facilitate scalable and flexible analysis of genetic variations.

Main Methods:

  • GenPop is a cross-platform web-based tool developed using PHP and JavaScript.
  • It incorporates the PHPExcel library for data handling and analysis.
  • The tool supports Hardy-Weinberg equilibrium tests, chi-square p-values, and SNP analysis.

Main Results:

  • GenPop enables analysis of single nucleotide polymorphisms (SNPs) under various inheritance models.
  • It performs descriptive analyses including odds ratios and relative risks at 95% confidence intervals.
  • The tool also analyzes multiple SNPs, including haplotype frequencies and linkage disequilibrium.

Conclusions:

  • GenPop offers a comprehensive solution for analyzing human population genetic data.
  • Its user-driven design and scalability make it adaptable for diverse research needs.
  • The tool supports case-control studies and various genetic association analyses.