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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,...
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.
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Related Experiment Video

Updated: Jun 3, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

RS-SNP: a random-set method for genome-wide association studies.

Annarita D'Addabbo1, Orazio Palmieri, Anna Latiano

  • 1Istituto di Studi sui Sistemi Intelligenti per l'Automazione - CNR, Bari, Italy.

BMC Genomics
|April 1, 2011
PubMed
Summary
This summary is machine-generated.

RS-SNP identifies gene sets enriched with moderately associated single-nucleotide polymorphisms (SNPs), offering a robust alternative for genetic association studies. This method enhances the detection of complex genetic contributions to diseases like Crohn's disease.

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Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
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Last Updated: Jun 3, 2026

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genomics

Background:

  • Traditional Genome-wide association (GWA) studies focus on identifying the most significant single-nucleotide polymorphisms (SNPs).
  • A novel approach, RS-SNP, is proposed to detect gene sets enriched in SNPs with moderate association to phenotypes, inspired by microarray data analysis.

Purpose of the Study:

  • To introduce and validate the RS-SNP method for identifying sets of genes enriched in associated SNPs.
  • To compare RS-SNP's performance against existing methods like GENGEN.

Main Methods:

  • RS-SNP assesses the statistical significance of the number of SNPs (p-value ≤ α) within a defined SNP set (S).
  • The method employs two null models: one assuming genotype-phenotype independence and another where SNP significance is independent of SNP identity within the set.
  • Non-parametric permutation tests are utilized for statistical significance assessment.

Main Results:

  • Application of RS-SNP to Crohn's disease (CD) data identified 86 pathways enriched in weakly associated SNPs using the MSigDB C2 CP collection.
  • 47 of these pathways were also identified by the GENGEN method.
  • RS-SNP analysis using the MSigDB C5 pathway collection yielded similar results, highlighting pathways with known links to CD and inflammatory diseases.

Conclusions:

  • RS-SNP is presented as a statistically sound and valuable alternative for SNP set enrichment analysis.
  • Experimental comparisons indicate RS-SNP is more robust against false positives than GENGEN.
  • The method effectively identifies biologically relevant pathways associated with complex diseases.