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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

17.9K
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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Genome-wide Association Studies-GWAS01:11

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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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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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...
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Genome Copying Errors02:46

Genome Copying Errors

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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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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Related Experiment Video

Updated: Aug 27, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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Published on: February 17, 2017

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PeakCNV: A multi-feature ranking algorithm-based tool for genome-wide copy number variation-association study.

Mahdieh Labani1,2, Ali Afrasiabi1, Amin Beheshti2

  • 1BioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.

Computational and Structural Biotechnology Journal
|September 23, 2022
PubMed
Summary
This summary is machine-generated.

PeakCNV accurately identifies true positive Copy Number Variation Regions (CNVRs) by reducing false positives using an independence ranking score. This tool enhances disease association studies by pinpointing biologically relevant CNVRs for conditions like prostate cancer and neurodevelopmental disorders.

Keywords:
Artificial intelligenceCNV association studyCopy number variationsGenetic abnormalitiesRisk genes

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Copy Number Variations (CNVs) are structural genomic alterations linked to various diseases.
  • Genome-wide association studies (GWAS) for CNVs are complicated by inconsistent CNV length and occurrence.
  • Copy Number Variation Regions (CNVRs) improve CNV-based GWAS but suffer from high false positive rates.

Purpose of the Study:

  • To develop PeakCNV, a novel tool to differentiate true positive CNVRs from false positives using an independence ranking score (IR-score).
  • To evaluate PeakCNV's performance against existing tools in identifying disease-associated CNVRs.

Main Methods:

  • Developed PeakCNV utilizing a feature ranking approach to calculate an IR-score.
  • Compared PeakCNV with other tools using CNV genotype data from prostate cancer and neurodevelopmental disorder cohorts.
  • Validated findings using FANTOM5 expression atlas and Clinical Genomic Database.

Main Results:

  • PeakCNV identified fewer, shorter risk CNVRs in prostate cancer cases compared to other tools, with a higher proportion of cases over healthy individuals.
  • The tool's accuracy was reproducible in neurodevelopmental disorder cohorts.
  • CNVRs identified by PeakCNV showed greater overlap with brain-enriched genes and genes associated with neurological conditions.

Conclusions:

  • PeakCNV effectively distinguishes true positive CNVRs, outperforming existing tools in identifying biologically meaningful CNVRs for disease association studies.
  • The tool provides a more accurate and reliable method for analyzing CNV-associated diseases.
  • PeakCNV is publicly available for research use.