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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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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

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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 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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Updated: Jun 29, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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Visualization for Diagnostic Review of Copy Number Variants in Complex DNA Sequencing Data.

Emilia Stahlbom, Jesper Molin, Claes Lundstrom

    IEEE Transactions on Visualization and Computer Graphics
    |April 8, 2024
    PubMed
    Summary
    This summary is machine-generated.

    Genomic data analysis for precision medicine requires efficient tools. Copycat is a new visualization environment that helps clinicians quickly review copy number variant (CNV) calls, improving genomic data interpretation.

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Medical Informatics

    Background:

    • Genomics is central to precision medicine, driving expectations for improved patient outcomes.
    • Clinical genomics, particularly DNA sequencing in oncology, is expanding, increasing the need for high-throughput data analysis.
    • Analyzing copy number variants (CNVs) algorithmically generates large candidate lists requiring manual review.

    Purpose of the Study:

    • To explore visualization concepts for clinical genomics data analysis.
    • To introduce Copycat, a visualization environment designed to aid manual review of CNV calls in a clinical setting.

    Main Methods:

    • Development of a visualization environment named Copycat.
    • Implementation of a scatter-glyph plot to replace traditional list visualizations.
    • Design of glyphs for rapid assessment of CNV call relevance.

    Main Results:

    • A prototype visualization environment, Copycat, was developed.
    • Formative evaluation of the Copycat prototype was conducted with domain specialists.
    • Insights were gathered to guide improvements in Copycat and general visualization for clinical genomics.

    Conclusions:

    • Effective visualization tools are crucial for managing the increasing volume of clinical genomics data.
    • The Copycat environment shows promise in streamlining the review of CNV calls.
    • User feedback from domain specialists is vital for developing practical clinical genomics visualization solutions.