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Related Concept Videos

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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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Single Nucleotide Polymorphisms-SNPs01:05

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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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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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Next-generation Sequencing03:00

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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Sanger Sequencing01:57

Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Related Experiment Video

Updated: Sep 11, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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Detection of Copy Number Alterations Using Single Cell Sequencing

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COPCNVBD: An Integrated Approach for Somatic Copy Number Variation and Breakpoint Detection Using Whole Genome

Yaoyao Li, Yajie Yan, Xiguo Yuan

    IEEE Transactions on Computational Biology and Bioinformatics
    |August 14, 2025
    PubMed
    Summary
    This summary is machine-generated.

    We developed COPCNVBD, an improved anomaly detection method for copy number variation (CNV) and breakpoint identification in whole genome sequencing data. It offers superior performance, especially with low tumor purity and coverage, aiding genomic analysis.

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    Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
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    Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
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    Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • Copy number variations (CNVs) are crucial in cancer genomics.
    • Existing read depth (RD) signal-based CNV detection methods are sensitive to measurement scales, parameters, and window sizes, affecting breakpoint accuracy.
    • Accurate detection of somatic CNVs and their breakpoints is essential for understanding cancer development.

    Purpose of the Study:

    • To propose COPCNVBD, an integrated approach for somatic CNV and breakpoint detection.
    • To improve upon the Copula-Based Outlier Detector (COPOD) for hyper-parameter-free CNV location inference.
    • To leverage pair-end mapping (PEM) reads for precise CNV breakpoint identification.

    Main Methods:

    • Developed COPCNVBD, integrating an improved COPOD for anomaly detection to infer CNV locations.
    • Utilized image boundary detection principles for precise CNV breakpoint localization.
    • Incorporated pair-end mapping (PEM) read information into a CNV breakpoint identification strategy.

    Main Results:

    • COPCNVBD demonstrated superior comprehensive performance on simulated datasets, particularly with low tumor purity and low coverage.
    • Evaluated on real cancer samples, COPCNVBD successfully detected moderate CNVs with high consistency.
    • The method showed robustness across varying tumor purity and sequencing coverage levels.

    Conclusions:

    • COPCNVBD offers an effective and robust solution for somatic copy number variation and breakpoint detection.
    • The proposed method performs well even with challenging low-purity and low-coverage genomic data.
    • COPCNVBD provides a valuable tool for genomic CNV analysis in research and clinical settings.