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Related Concept Videos

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...
Karyotyping01:17

Karyotyping

Describing the number and physical features of chromosomes can reveal abnormalities that underlie genetic diseases. This description is facilitated by special staining techniques that produce a particular banding pattern on each chromosome. State-of-the-art techniques make this approach even more powerful, enabling the detection of individual genes that cause disease.A Simple Chromosome Staining Technique Provides Valuable Scientific InsightSome genetic diseases can be detected by looking at...
Karyotyping01:17

Karyotyping

Describing the number and physical features of chromosomes can reveal abnormalities that underlie genetic diseases. This description is facilitated by special staining techniques that produce a particular banding pattern on each chromosome. State-of-the-art techniques make this approach even more powerful, enabling the detection of individual genes that cause disease.A Simple Chromosome Staining Technique Provides Valuable Scientific InsightSome genetic diseases can be detected by looking at...

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Related Experiment Video

Updated: Jul 2, 2026

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
09:16

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

CGcgh: a tool for molecular karyotyping using DNA microarray-based comparative genomic hybridization (array-CGH).

Yun-Shien Lee1, Angel Chao, An-Shine Chao

  • 1Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Tao-Yuan, Taiwan.

Journal of Biomedical Science
|August 21, 2008
PubMed
Summary

A new MATLAB-based program, CGcgh, analyzes DNA copy number variations using microarray-based comparative genomic hybridization (array-CGH). This tool aids in detecting chromosomal abnormalities in various human samples, enhancing genomic research.

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Last Updated: Jul 2, 2026

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
09:16

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization
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Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants
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An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants

Published on: November 8, 2017

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Microarray-based comparative genomic hybridization (array-CGH) is crucial for analyzing DNA copy number variations.
  • Existing methods require user-friendly tools for efficient analysis of chromosomal amplifications and deletions.
  • Applications include fetal aneuploidies and cancer tissue analysis.

Purpose of the Study:

  • To develop and present a user-friendly, standalone PC software for array-CGH data analysis.
  • To provide an automated method for identifying abnormal DNA copy numbers using statistical approaches.
  • To validate the software's performance across diverse human genomic samples.

Main Methods:

  • Development of a MATLAB-based program, CGcgh, for array-CGH analysis.
  • Implementation of automated detection of copy number gains and losses using sliding window t-tests.
  • Graphical display of chromosomal data with options for G-banding ideogram integration.

Main Results:

  • CGcgh successfully analyzed karyotype-confirmed human samples, including trisomies and publicly available microarray data.
  • The software accurately detected copy number changes in small genomic regions.
  • CGcgh demonstrated compatibility with various microarray platforms (cDNA, oligonucleotide, Affymetrix).

Conclusions:

  • CGcgh is an effective and accessible tool for analyzing array-CGH data.
  • The software aids clinical geneticists in identifying copy number variations.
  • CGcgh supports multiple microarray formats and is freely downloadable.