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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 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.
Karyotyping01:17

Karyotyping

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Karyotyping01:17

Karyotyping

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Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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: May 22, 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

arrayMap: a reference resource for genomic copy number imbalances in human malignancies.

Haoyang Cai1, Nitin Kumar, Michael Baudis

  • 1Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.

Plos One
|May 26, 2012
PubMed
Summary
This summary is machine-generated.

arrayMap is a new database that provides a comprehensive collection of human cancer copy number profiling data. This resource enables meta-analysis and data integration for genomic feature mining across diverse cancer types.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Genomic copy number abnormalities (CNAs) are crucial for identifying tumor suppressor genes, oncogenes, and clinical markers in cancer.
  • High-resolution microarray techniques have advanced CNA mapping, yet a centralized resource for oncogenomic array data is lacking.

Purpose of the Study:

  • To introduce arrayMap, a curated reference database and bioinformatics resource for human cancer copy number profiling data.
  • To provide a platform for meta-analysis and systems-level integration of high-resolution oncogenomic CNA data.

Main Methods:

  • Compiled over 40,000 arrays from 224 cancer types from various sources (GEO, ArrayExpress, TCGA, publications, direct submissions).
  • Integrated probe-level data with visualization tools for gene-level and genome-wide analysis.
  • Enabled downstream data analysis and visualization for multi-case selections.

Main Results:

  • arrayMap offers a vast collection of human cancer CNA data.
  • The database facilitates integrated analysis and visualization of genomic data.
  • Data is accessible for mining genomic features across a wide range of cancer entities.

Conclusions:

  • arrayMap addresses the need for an extensive, accessible resource for high-resolution oncogenomic CNA data.
  • It serves as a long-term platform for oncogenomic data, independent of specific platforms or projects.
  • The online database is available at http://www.arraymap.org.