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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...
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...
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Genome Size and the Evolution of New Genes03:21

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
Genetic Variation01:25

Genetic Variation

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.
Genes exist in different versions called alleles, which...
Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...

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Related Experiment Video

Updated: Jul 5, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Gene-centric genomewide association study via entropy.

Yuehua Cui1, Guolian Kang, Kelian Sun

  • 1Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA. cui@stt.msu.edu <cui@stt.msu.edu>

Genetics
|May 7, 2008
PubMed
Summary
This summary is machine-generated.

A novel gene-centric entropy test offers a powerful approach for genomewide association studies. This method enhances disease gene identification by analyzing variants within genes simultaneously, improving replication rates.

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Last Updated: Jul 5, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

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Published on: August 21, 2016

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Area of Science:

  • Genetics
  • Statistical Genomics
  • Bioinformatics

Background:

  • Genetic variants within genes are crucial for disease risk assessment.
  • Current association studies often face replication challenges due to reliance on linkage disequilibrium.
  • Existing methods may not adequately capture the impact of multiple variants within a single gene.

Purpose of the Study:

  • To introduce a gene-centric approach using entropy statistics for genomewide association studies (GWAS).
  • To develop a robust method for identifying disease genes by considering all genic variants collectively.
  • To improve the power and replicability of genetic association findings.

Main Methods:

  • Developed an entropy-based statistical test for association analysis.
  • Incorporated a joint genotype distribution model for variants within a gene.
  • Utilized a grouping algorithm with penalized entropy to reduce dimensionality.

Main Results:

  • The entropy test demonstrated stable power across various disease models with adequate sample sizes.
  • The gene-centric approach showed significantly greater power compared to single SNP analysis, particularly for genes with multiple disease variants.
  • Extensive simulations confirmed the reliability and efficiency of the proposed method.

Conclusions:

  • The entropy-based gene-centric approach provides a robust and computationally efficient strategy for GWAS.
  • This method enhances the identification of disease genes by accounting for multiple variants simultaneously.
  • It offers a promising alternative for future genomewide genetic association studies as genic SNP data becomes more comprehensive.