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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 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.
Genetic Variation01:25

Genetic Variation

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, which...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jun 29, 2026

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

CNVDetector: locating copy number variations using array CGH data.

Peng-An Chen1, Hsiao-Fei Liu, Kun-Mao Chao

  • 1Department of Computer Science and Information Engineering, Graduate Institute of Biomedical Electronics and Bioinformatics and Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan.

Bioinformatics (Oxford, England)
|October 10, 2008
PubMed
Summary
This summary is machine-generated.

CNVDetector identifies copy number variations (CNVs) in genomes. This program handles noisy data, offers fast processing, and provides statistical significance for each CNV call.

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Related Experiment Videos

Last Updated: Jun 29, 2026

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

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Published on: February 17, 2017

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
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Published on: August 24, 2017

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Copy Number Variations (CNVs) are significant genomic alterations.
  • Accurate CNV detection is crucial for understanding genetic diseases.

Purpose of the Study:

  • To introduce CNVDetector, a novel program for CNV detection.
  • To highlight the advantages of CNVDetector over existing methods.

Main Methods:

  • CNVDetector utilizes a linear time kernel for efficient processing.
  • The program is designed to handle array comparative genomic hybridization (aCGH) data.
  • It accommodates data with non-normally distributed noise.

Main Results:

  • CNVDetector successfully locates CNVs in single genomes.
  • The program offers easily selectable parameters for user convenience.
  • Statistical significance is evaluated for each identified CNV.

Conclusions:

  • CNVDetector is a robust and efficient tool for CNV detection.
  • Its ability to handle noisy data and provide statistical significance makes it valuable for genomic research.