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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...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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,...

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Related Experiment Video

Updated: Jun 14, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

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Published on: June 23, 2012

Approaches for evaluating rare polymorphisms in genetic association studies.

Qizhai Li1, Hong Zhang, Kai Yu

  • 1Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.

Human Heredity
|March 25, 2010
PubMed
Summary

This study introduces novel statistical methods for analyzing rare genetic variants in complex diseases. These new approaches improve upon existing methods, offering better insights into the genetic underpinnings of diseases by considering variants with low minor allele frequency.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Area of Science:

  • Genetics
  • Biostatistics
  • Genomic Medicine

Background:

  • Current genetic association studies prioritize common single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) >5% based on the common-disease-common-variant (CDCV) hypothesis.
  • The CDCV hypothesis posits that common diseases stem from common variants with small to moderate effects.
  • Emerging evidence indicates that causal genetic polymorphisms for complex diseases, including SNPs and copy number variants (CNVs), exhibit a wide MAF spectrum, from rare to common.

Purpose of the Study:

  • To address the lack of statistical approaches for analyzing rare genetic variants.
  • To propose and evaluate novel statistical methods specifically designed for the analysis of rare variants in genetic association studies.
  • To provide more accurate and powerful tools for identifying genetic loci associated with complex diseases, considering the full spectrum of variant frequencies.

Main Methods:

  • Development of two novel statistical approaches tailored for the analysis of rare genetic variants.
  • Utilizing simulation studies to rigorously assess the performance of the proposed methods under various scenarios.
  • Application of the new methods to two real-world genetic datasets to demonstrate their practical utility and advantages.

Main Results:

  • The proposed methods demonstrate significant advantages over existing approaches for analyzing rare genetic variants.
  • Simulation studies confirm the improved accuracy and power of the novel methods compared to traditional techniques.
  • Real data examples illustrate the effectiveness of the new approaches in identifying disease-associated genetic loci.

Conclusions:

  • The developed statistical methods offer a valuable advancement for genetic association studies involving rare variants.
  • These novel approaches enhance the ability to uncover the genetic architecture of complex diseases by incorporating rare variants.
  • The findings suggest a need to broaden the focus beyond common variants in genetic research for complex diseases.