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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%...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

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Related Experiment Video

Updated: Jun 26, 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

Association tests and software for copy number variant data.

Vincent Plagnol1

  • 1JDRF/WT Diabetes and Inflammation Laboratory, Addenbrooke's Hospital, Cambridge, UK. vincent.plagnol@cimr.cam.ac.uk

Human Genomics
|January 24, 2009
PubMed
Summary
This summary is machine-generated.

Copy number variation (CNV) plays a key role in common genetic disorders. New methods are needed for CNV association studies, especially when raw data is more reliable than discrete calls.

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Copy number variation (CNV) is increasingly recognized for its contribution to common genetic disorders.
  • Single nucleotide polymorphisms (SNPs) imperfectly tag CNVs, necessitating direct CNV association studies.
  • Existing assays allow direct CNV assessment in large cohorts for statistical power.

Purpose of the Study:

  • To review available programs for copy number variation association testing.
  • To address challenges in CNV association studies arising from assay data quality.
  • To highlight the utility of raw continuous CNV data over discrete calls when assay quality is limited.

Main Methods:

  • Review of existing statistical methods and software for CNV association testing.
  • Comparison of association tests using discrete CNV calls versus raw continuous measurements.
  • Evaluation of methods applicable to case-control and family-based study designs.

Main Results:

  • Association tests for CNV data share similarities with SNP-based tests.
  • Technological limitations in current CNV assays often yield ambiguous discrete calls.
  • Raw continuous CNV measurements can provide more accurate association results than discrete calls.

Conclusions:

  • The development of novel statistical methods is crucial for accurate CNV association testing.
  • Utilizing raw continuous data is recommended when CNV assay quality is suboptimal.
  • This review provides a guide to current CNV association testing programs for researchers.