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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...

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Related Experiment Video

Updated: May 25, 2026

Oncogenic Gene Fusion Detection Using Anchored Multiplex Polymerase Chain Reaction Followed by Next Generation Sequencing
09:49

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Published on: July 5, 2019

Evaluating translocation gene fusions by SNP array data.

Hong Liu1, Asher Zilberstein, Pascal Pannier

  • 1Lead Generation to Candidate Realization, Sanofi, Route 202-206, Bridgewater, NJ 08807 USA.

Cancer Informatics
|January 20, 2012
PubMed
Summary
This summary is machine-generated.

Single nucleotide polymorphism (SNP) array data can predict genetic translocations in tumors. This study identified copy number breakpoints in cancer cell lines and patient samples, revealing candidate oncogenes linked to translocations.

Keywords:
SNP arraycopy number breakpointcopy number variationtranslocation

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Area of Science:

  • Genomics
  • Cancer Biology
  • Bioinformatics

Background:

  • Somatic genetic alterations drive tumor development.
  • Identifying chromosomal translocations is crucial but challenging.
  • High-density SNP microarrays detect DNA copy number variation (CNV).

Purpose of the Study:

  • To evaluate SNP array data for predicting genetic translocations.
  • To identify copy number breakpoints in known fusion genes.
  • To discover novel translocation-associated oncogenes.

Main Methods:

  • Utilized SNP array data from cancer cell lines and patient samples.
  • Analyzed CNV and copy number breakpoints for fusion genes.
  • Performed genome-wide analysis across 820 cancer cell lines.

Main Results:

  • SNP array data effectively predicted genetic aberrations from translocations.
  • Identified copy number breakpoints within target genes.
  • Discovered candidate oncogenes associated with potential translocations.

Conclusions:

  • SNP array analysis is a viable method for predicting tumor translocations.
  • This approach aids in identifying novel oncogenes in cancer.
  • Further research can leverage SNP data for translocation detection.