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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%...

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Related Experiment Video

Updated: May 28, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Functional enrichment analysis with structural variants: pitfalls and strategies.

C Webber1

  • 1Department of Physiology, Anatomy and Genetics, MRC Functional Genomics Unit, University of Oxford, Oxford, UK. caleb.webber@dpag.ox.ac.uk

Cytogenetic and Genome Research
|October 15, 2011
PubMed
Summary

Functional enrichment analysis aids understanding of human structural variation

Area of Science:

  • Genomics
  • Human Genetics
  • Bioinformatics

Background:

  • Interpreting phenotypic consequences of human structural variation is complex.
  • Functional enrichment analysis offers insights into genotype-phenotype relationships by identifying gene sets affected by structural variants.

Purpose of the Study:

  • This review discusses approaches and choices for applying functional enrichment analysis to human structural variation.
  • It highlights potential biases and the importance of understanding analytical expectations.

Main Methods:

  • The review examines critical choices in functional enrichment analysis for structural variants.
  • Key considerations include background distribution selection, gene selection criteria, and tissue-specific gene length biases.

More Related Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Related Experiment Videos

Last Updated: May 28, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Main Results:

  • Functional enrichment analysis is a valuable tool for biological insights into structural variation.
  • Careful methodological choices are crucial to mitigate bias and ensure accurate interpretation.

Conclusions:

  • Addressing biases in functional enrichment analysis is essential for accurate genotype-phenotype correlation in human structural variation studies.
  • Understanding analytical assumptions improves the reliability of findings.