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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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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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Efficient Identification of Null-Allele Single Nucleotide Polymorphism Markers.

Umut Özbek¹, Eleanor Feingold, Daniel E Weeks

¹Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, N.Y., USA.

|November 28, 2015

Summary

Identifying null-allele SNPs, which can be discarded in genome-wide association studies, is crucial. These identified SNPs can then be used for genotype-phenotype association testing or copy number variation analysis.

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Area of Science:

Genetics
Bioinformatics

Background:

Genome-wide association studies (GWAS) often discard markers failing quality control.
Null alleles, leading to deviations from Hardy-Weinberg equilibrium (HWE), are a common reason for marker exclusion.
Identifying null-allele single nucleotide polymorphisms (SNPs) can reveal valuable genetic information.

Purpose of the Study:

To develop a computational model for identifying null-allele SNPs from chip-based genotype data.
To integrate this model with standard HWE analysis for robust SNP classification.

Main Methods:

A novel model for chip-based genotype data with null alleles was developed.
Supervised learning algorithms, including Support Vector Machines (SVM), Classification and Regression Trees (CART), and Random Forests, were employed.
The proposed model was combined with the standard HWE model for classification.

Main Results:

A list of null-allele SNPs was successfully identified on the Illumina 660W-Quad chip.
The study provides practical guidance for applying the CART model to diverse SNP datasets.

Conclusions:

Accurate identification of null-allele SNPs enhances their utility in genetic research.
These SNPs can be leveraged for genotype-phenotype association studies.
Null-allele SNPs are valuable for detecting copy number variations.