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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...
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,...
Probability Laws01:49

Probability Laws

Overview
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%...
Hazard Ratio01:12

Hazard Ratio

The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial evaluating a...
Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
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Related Experiment Video

Updated: May 15, 2026

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

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

SNP prioritization using a Bayesian probability of association.

John R Thompson1, Martin Gögele, Christian X Weichenberger

  • 1Department of Health Sciences, University of Leicester, Leicester, United Kingdom. john.thompson@le.ac.uk

Genetic Epidemiology
|January 3, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new Bayesian method for prioritizing genetic variants (SNPs) in genome-wide association studies. This approach combines multiple data sources for more reproducible and interpretable results than P-values alone.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

Area of Science:

  • Genetics and Genomics
  • Statistical Bioinformatics
  • Human Disease Association Studies

Background:

  • Genome-wide association studies (GWAS) typically prioritize single nucleotide polymorphisms (SNPs) using P-values.
  • Incorporating external annotation data for SNP prioritization is common but often subjective and difficult to reproduce.
  • Previous work identified 14 key types of external information relevant to SNP prioritization.

Purpose of the Study:

  • To develop a formalized, reproducible method for prioritizing candidate genes or SNPs from GWAS.
  • To create an approximate Bayesian analysis for estimating the probability of association, integrating diverse data sources.
  • To improve upon P-value-based SNP selection by providing a more interpretable and power-aware metric.

Main Methods:

  • An approximate Bayesian analysis was developed to estimate the probability of association for SNPs.
  • The calculation integrates four information sources: genome-wide data, bioinformatics SNP annotations, empirical SNP weights, and prior opinions.
  • The method is computationally efficient, suitable for analyzing millions of SNPs, and makes subjective judgments explicit for reproducibility.

Main Results:

  • The developed probability of association offers a more intuitive interpretation than traditional P-values.
  • This metric accounts for study power, providing a more nuanced assessment of SNP significance.
  • Application to a kidney function GWAS meta-analysis demonstrated superior SNP selection performance compared to using P-values alone.

Conclusions:

  • The approximate Bayesian approach provides a robust and reproducible method for SNP prioritization in GWAS.
  • The probability of association is a more informative metric than P-values for selecting promising SNPs for further investigation.
  • This method enhances the efficiency and reliability of genetic discovery in large-scale association studies.