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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.

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Related Experiment Video

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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

A flexible rank-based framework for detecting copy number aberrations from array data.

Thomas LaFramboise1, Wendy Winckler, Roman K Thomas

  • 1Department of Genetics, Case Western Reserve University, Cleveland, OH 44106, USA. Thomas.LaFramboise@case.edu

Bioinformatics (Oxford, England)
|January 30, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a robust rank-based method for detecting DNA copy number aberrations, including deletions and gains, from array data. The approach offers high sensitivity and is applicable across various platforms for disease research.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • DNA copy number aberrations are implicated in numerous human diseases.
  • Accurate copy number characterization is crucial for disease research.
  • High-throughput array platforms are key tools for measuring DNA copy number.

Purpose of the Study:

  • To develop a robust, nonparametric rank-based method for detecting DNA copy number aberrations.
  • To enable the reliable assignment of statistical significance to detected genomic alterations.
  • To demonstrate the method's flexibility and performance across different array platforms.

Main Methods:

  • Utilized nonparametric rank-based statistics to analyze raw array copy number measurements.
  • Developed three distinct statistics to identify somatic lesions, germline deletions, and germline gains.
  • Applied the framework to data from single nucleotide polymorphism arrays and array comparative genomic hybridization.

Main Results:

  • Presented a simple yet powerful rank-based approach for detecting DNA copy number deletions and gains.
  • Demonstrated the method's robustness and statistical rigor, allowing for meaningful significance assignment.
  • Showcased favorable comparisons with established methods on well-characterized samples and high sensitivity in power simulations.

Conclusions:

  • The developed rank-based framework is flexible and platform-independent.
  • Reliably detects inherited, de novo, and somatic gains or losses of genomic DNA.
  • An R package, RankCopy, is available for implementing these methods.