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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%...
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...
Pedigree Analysis01:35

Pedigree Analysis

Overview
Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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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Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Bayesian model to detect phenotype-specific genes for copy number data.

Juan R González1, Carlos Abellán, Juan J Abellán

  • 1Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain. jrgonzalez@creal.cat

BMC Bioinformatics
|June 15, 2012
PubMed
Summary

This study introduces a Bayesian model to identify specific genetic variants, like copy number variants (CNVs), across different human groups. The model aids in understanding disease predisposition and treatment response by analyzing genetic data more effectively.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genomics

Background:

  • Identifying group-specific genetic variants, particularly copy number variants (CNVs), is crucial for understanding disease predisposition and drug response.
  • Thousands of CNVs require analysis, with only a few expected to associate with specific phenotypes.

Purpose of the Study:

  • To propose a novel Bayesian model for analyzing genetic variants, specifically CNVs, across diverse individual groups.
  • To elucidate differences in disease susceptibility and response to pharmaceutical treatments based on genetic variations.

Main Methods:

  • A Bayesian statistical model was developed to analyze thousands of copy number variants (CNVs).
  • The model was applied to HapMap data from three major human groups and extended to adjust for confounding covariates like population stratification.
  • An R package, bayesGen, was created to implement the model and estimation algorithms.

Main Results:

  • The model successfully identified specific CNVs related to treatment response in ovarian cancer patients.
  • A simulation study demonstrated that the proposed model outperforms existing approaches for analyzing common copy-number polymorphisms (CNPs) and complex CNVs.
  • The model's effectiveness was illustrated using HapMap data from three major human groups.

Conclusions:

  • The developed Bayesian model effectively discovers specific genetic variants differentiating subgroups of individuals.
  • The model can be applied to studies with or without control groups, integrating data to identify phenotype-associated and shared genes.
  • This approach aids in understanding genetic contributions to disease and treatment outcomes.