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Comparing Copy Number Variations and SNPs02:26

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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.
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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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Updated: Dec 11, 2025

Detection of Copy Number Alterations Using Single Cell Sequencing
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reconCNV: interactive visualization of copy number data from high-throughput sequencing.

Raghu Chandramohan1, Nipun Kakkar2, Angshumoy Roy2,3,4,5

  • 1Department of Molecular and Human Genetics, Houston, TX 77030, USA.

Bioinformatics (Oxford, England)
|August 22, 2020
PubMed
Summary
This summary is machine-generated.

reconCNV offers interactive visualization for copy number variation (CNV) detected in next-generation sequencing (NGS) data. This tool generates an annotated web-based dashboard for efficient CNV analysis in research and clinical settings.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Copy number variation (CNV) represents a significant category of unbalanced structural rearrangements in the genome.
  • Existing methods for CNV detection in high-throughput targeted sequencing are advanced, yet interactive visualization tools are lacking.
  • Efficient interpretation of CNV data is crucial for both research and clinical applications.

Purpose of the Study:

  • To introduce reconCNV, a novel tool for interactive and dynamic visualization of CNVs from next-generation sequencing (NGS) data.
  • To provide a user-friendly, web-based dashboard for summarizing and viewing CNV findings.
  • To enhance the interpretation of CNV data by integrating features for allelic imbalance and technical artifact masking.

Main Methods:

  • Developed reconCNV, a tool generating an interactive, annotated, web-based HTML dashboard.
  • Designed reconCNV to be compatible with delimited result files from various NGS CNV callers.
  • Incorporated features for visualizing relative fold change, absolute copy number, and variant allele fraction.

Main Results:

  • reconCNV produces a standalone HTML file viewable in any web browser, requiring no backend server.
  • The tool visualizes CNVs, allelic imbalance, and loss of heterozygosity.
  • Includes functionalities to mask technical artifacts and link to the UCSC Genome Browser for augmented review.

Conclusions:

  • reconCNV facilitates efficient visualization and interpretation of NGS CNV data.
  • The tool serves as a light-weight plugin, easily integrated into existing analysis pipelines.
  • Enhances CNV analysis in both research and clinical settings through interactive and annotated outputs.