Genetics and Population Analysis

  • Prachi Balyan
  • , Nismabi A. Nisamudheen
  • , Jan Zainab
  • , Dinesh Velayutham
  • , Manoj K. Balyan*
  • , Puthen V. Jithesh*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Population genetic analysis is a powerful tool for understanding genetic diversity, evolution, and disease susceptibility across human populations. It involves studying genetic variation within and between populations, identifying patterns of inheritance, and inferring the underlying evolutionary processes that shape the genetic diversity. Genome wide association studies are widely used and have shown remarkable potential to associate thousands of common genetic variants with human traits or diseases. The rapid advancements in genomic technologies, statistical methods and algorithms have largely enabled the understanding of patterns of genetic variation within and between populations, population structure and history. This chapter provides an overview of fundamental principles and key parameters in population genetics and further explores genetics and population analysis by providing an overview of methods, programs and tools for studying and analyzing genetic diversity and population structure. The genetic variations in human populations are explored with illustrative case studies to provide an insight into the structure of genetic variations across diverse populations and actionable genetic variants in a population.

Original languageEnglish
Title of host publicationEncyclopedia of Bioinformatics and Computational Biology
PublisherElsevier
PagesVol6:463-Vol6:483
ISBN (Electronic)9780323955027
ISBN (Print)9780323955034
DOIs
Publication statusPublished - 1 Jan 2025

Keywords

  • Effective population size
  • Genetic diversity
  • Genetic variation
  • GWAS
  • Haplotype phasing
  • Hardy-Weinberg equilibrium
  • Linkage disequilibrium
  • Population genetics
  • Population structure
  • Population-scale genome sequencing

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