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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.
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%...
Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

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Related Experiment Video

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Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Functional analysis of HapMap SNPs.

Ching-Ti Liu1, Houwei Lin, Honghuang Lin

  • 1Department of Biostatistics, Boston University, Boston, MA 02118, USA.

Gene
|October 9, 2012
PubMed
Summary
This summary is machine-generated.

HapMap SNPs offer good gene coverage but lack functional insights for complex diseases. A new SNP panel is needed to better identify disease-causing genetic variants in future studies.

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Published on: June 23, 2012

Area of Science:

  • Genetics
  • Genomics
  • Bioinformatics

Background:

  • Genome-wide association studies (GWAS) identify genetic variants linked to complex diseases.
  • Understanding the functional impact of these variants is crucial but often limited.
  • HapMap SNPs are widely used as a reference panel in GWAS.

Purpose of the Study:

  • To systematically analyze the functional characteristics of HapMap Single Nucleotide Polymorphisms (SNPs).
  • To identify subsets of genetic variants with significant functional implications for disease research.
  • To evaluate the utility of HapMap SNPs as a reference panel for GWAS.

Main Methods:

  • Systematic functional analysis of HapMap SNPs.
  • Assessment of SNP coverage within RefSeq genes and gene deserts.
  • Identification of non-synonymous SNPs and functionally important variants.

Main Results:

  • HapMap SNPs demonstrate good coverage within RefSeq genes, including disease-related genes.
  • A small proportion of HapMap SNPs are non-synonymous; many are located in gene deserts.
  • Numerous functionally important variants remain unexamined within the current HapMap panel.

Conclusions:

  • HapMap SNPs provide valuable but incomplete functional information for GWAS.
  • A revised SNP reference panel incorporating additional functional variants is recommended.
  • Improved SNP panels will enhance the identification of disease-causal variants in future GWAS.