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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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.
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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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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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Genome Copying Errors02:46

Genome Copying Errors

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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.
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Genetic Variation01:25

Genetic Variation

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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...
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Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Related Experiment Video

Updated: Apr 29, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
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A sequential Monte Carlo framework for haplotype inference in CNV/SNP genotype data.

Alexandros Iliadis1, Dimitris Anastassiou1, Xiaodong Wang1

  • 1Department of Electrical Engineering, Center for Computational Biology Bioinformatics and Columbia University, New York, NY 10027, USA.

EURASIP Journal on Bioinformatics & Systems Biology
|May 29, 2014
PubMed
Summary
This summary is machine-generated.

New software, Tree-Based Deterministic Sampling CNV (TDSCNV), efficiently infers haplotypes from copy number variation (CNV) and single-nucleotide polymorphism (SNP) data. This advancement aids in understanding disease etiology by improving genetic analysis.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Copy number variations (CNVs) are prevalent in the human genome and linked to complex traits and diseases.
  • Genome-wide association studies (GWAS) utilize single-nucleotide polymorphism (SNP) data, but integrating CNVs is crucial for comprehensive genetic analysis.
  • Current computational tools lack efficient methods for haplotype inference in combined CNV/SNP datasets.

Purpose of the Study:

  • To develop a novel computational framework for inferring haplotypes from integrated CNV and SNP data.
  • To address the limitations of existing software in handling complex genomic datasets.
  • To provide a faster and scalable solution for genetic association studies involving CNVs and SNPs.

Main Methods:

  • Introduction of Tree-Based Deterministic Sampling CNV (TDSCNV), a framework utilizing a sequential Monte Carlo sampling scheme.
  • Comparison of TDSCNV performance against polyHap(v2.0), the existing software for CNV/SNP haplotype inference.
  • Evaluation on datasets with varying numbers of genetic markers.

Main Results:

  • TDSCNV demonstrates comparable accuracy to polyHap(v2.0) in haplotype inference.
  • TDSCNV is significantly faster, operating an order of magnitude quicker than polyHap(v2.0).
  • TDSCNV exhibits linear scalability with respect to the number of markers and individuals.

Conclusions:

  • TDSCNV offers a computationally efficient and scalable method for haplotype inference in CNV/SNP data.
  • This advancement facilitates more robust genetic association studies and disease etiology research.
  • TDSCNV is recommended as a preferred tool for analyzing complex genomic datasets.