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Related Concept Videos

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%...
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,...
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...

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Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

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Bayesian EM algorithm for scoring polymorphic deletions from SNP data and application to a common CNV on 8q24.

Sebastian Zöllner1, Gang Su, William C L Stewart

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109-2029, USA. szoellne@umich.edu

Genetic Epidemiology
|December 17, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method to identify copy number variations (CNVs) and their association with diseases. The method accurately inferred CNV carrier status but found no link between a specific CNV and bipolar disorder.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical genomics

Background:

  • Copy number variations (CNVs) are significant sources of genetic diversity and potential disease associations.
  • Evaluating CNV carrier status typically involves analyzing SNP genotyping data, but robust statistical methods are needed.

Purpose of the Study:

  • To develop and validate a novel statistical method for inferring CNV carrier status using SNP genotyping data and signal intensity.
  • To assess the association between a specific CNV in the 8q24 region and bipolar disorder.

Main Methods:

  • A Bayesian approach was used to calculate posterior probabilities of CNV carrier status by integrating genotype and hybridization intensity data.
  • Signal intensity was modeled using a mixture of normal distributions, with parameters estimated via an expectation-maximization (EM) algorithm.
  • The method was applied to a dataset of 3,512 individuals with a known deletion on chromosome 8q24.

Main Results:

  • The novel method accurately inferred carrier status for a common deletion on 8q24 in 3,512 individuals, identifying 172 heterozygous and 1 homozygous deletion carrier.
  • No significant association was found between bipolar disorder and carrier status for this specific CNV.
  • The algorithm precisely identified CNV boundaries and demonstrated power in detecting shorter CNVs.

Conclusions:

  • The developed statistical method provides a robust and accurate approach for inferring CNV carrier status and identifying CNV boundaries.
  • The study did not find evidence supporting an association between the 8q24 deletion and bipolar disorder in the analyzed sample.
  • The method shows promise for broader applications in CNV analysis and disease association studies.