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Genome-wide Association Studies-GWAS

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-SNPs

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 SNPs

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%...

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Related Experiment Video

Updated: Jun 8, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Assessing consistency between versions of genotype-calling algorithm Birdseed for the Genome-Wide Human SNP Array 6.0

Huixiao Hong¹, Lei Xu, Weida Tong

¹Center for Toxicoinformatics, Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. Huixiao.Hong@fda.hhs.gov

Advances in Experimental Medicine and Biology

|September 25, 2010

Summary

Genotype calling consistency between two Birdseed algorithm versions for Affymetrix SNP Array 6.0 was assessed. Minor genotype differences between Birdseed versions propagated to downstream genome-wide association studies (GWAS).

Related Experiment Videos

Last Updated: Jun 8, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

Genetics
Bioinformatics
Genomics

Background:

Accurate genotype calling is crucial for reliable genome-wide association studies (GWAS).
Errors in genotype calling can lead to false associations between genotype and phenotype.
The Affymetrix Genome-Wide Human SNP Array 6.0 is a commonly used platform for GWAS.

Purpose of the Study:

To assess genotype calling reproducibility between two versions of the Birdseed algorithm.
To examine how genotype inconsistencies between Birdseed versions impact downstream association analysis.

Main Methods:

Utilized the Birdseed genotype-calling algorithm on the Affymetrix Genome-Wide Human SNP Array 6.0.
Compared genotype calls between Birdseed version 1 and version 2 using 270 HapMap samples.
Evaluated the propagation of genotype inconsistencies into association analysis.

Main Results:

Identified slight differences in genotypes called by Birdseed version 1 and version 2.
Demonstrated that these genotype inconsistencies propagate to downstream association analyses.

Conclusions:

The reproducibility of genotype calling between Birdseed versions is not perfect.
Genotype inconsistencies can affect the reliability of GWAS results, necessitating careful consideration of algorithm versions.