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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 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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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.
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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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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: Jan 1, 2026

Visualizing Genetic Variants, Short Targets, and Point Mutations in the Morphological Tissue Context with an RNA In Situ Hybridization Assay
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Paragraph: a graph-based structural variant genotyper for short-read sequence data.

Sai Chen1, Peter Krusche2,3, Egor Dolzhenko1

  • 1Illumina Inc, 5200 Illumina Way, San Diego, CA, USA.

Genome Biology
|December 21, 2019
PubMed
Summary
This summary is machine-generated.

Paragraph accurately genotypes structural variations (SVs) using sequence graphs. This novel tool improves SV detection in genomics research and clinical sequencing, outperforming existing methods in large-scale population studies.

Keywords:
Population studiesSequence graphsStructural variationTargeted variant calling

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Accurate detection and genotyping of structural variations (SVs) are critical for genomics research and clinical diagnostics.
  • Short-read sequencing data presents challenges for comprehensive SV analysis.

Purpose of the Study:

  • To introduce Paragraph, a novel genotyper for accurate SV detection and genotyping from short-read data.
  • To evaluate Paragraph's performance against existing methods using diverse genomic datasets.

Main Methods:

  • Paragraph models structural variations using sequence graphs and annotation data.
  • Performance was validated on whole-genome sequencing data using long-read SV calls as a reference.
  • The tool was applied to a cohort of 100 diverse, short-read sequenced samples.

Main Results:

  • Paragraph demonstrates superior accuracy in SV detection and genotyping compared to current genotypers.
  • The tool effectively handles diverse ancestry samples in population-scale analyses.
  • Validation using long-read data confirmed Paragraph's high precision.

Conclusions:

  • Paragraph offers a significant advancement in SV genotyping from short-read sequencing.
  • The tool is suitable for large-scale genomic studies and clinical applications.
  • This method enhances the utility of short-read data for structural variation analysis.