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Related Concept Videos

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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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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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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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: Dec 20, 2025

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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SVJedi: genotyping structural variations with long reads.

Lolita Lecompte1, Pierre Peterlongo1, Dominique Lavenier1

  • 1Univ Rennes, Inria, CNRS, IRISA, F-35000 Rennes, France.

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

SVJedi accurately genotypes known structural variants (SVs) in long read sequencing data. This novel method improves SV genotyping accuracy compared to existing tools and approaches.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Structural variants (SVs) are increasingly discovered in the human genome using advanced sequencing technologies.
  • Accurate genotyping of known SVs is crucial for clinical applications.
  • Existing tools for SV genotyping are primarily designed for short-read data, leaving a gap for long-read sequencing.

Purpose of the Study:

  • To develop a novel method for genotyping known structural variants (SVs) from long-read sequencing data.
  • To provide a dedicated tool, SVJedi, for assessing the presence and frequency of known SVs in long-read samples.

Main Methods:

  • Generation of representative allele sequences for each structural variant.
  • Alignment of long reads to these allele sequences.
  • Analysis and filtering of alignments to quantify SV allele presence and frequencies.

Main Results:

  • SVJedi achieves high genotyping accuracy on both simulated and real human datasets.
  • SVJedi demonstrates superior performance compared to other existing long-read genotyping tools.
  • The tool significantly improves SV genotyping compared to SV discovery and short-read approaches.

Conclusions:

  • SVJedi offers a robust solution for accurate SV genotyping using long-read sequencing.
  • The method enhances the utility of long-read data for clinical diagnostics and genomic research.
  • SVJedi represents a significant advancement in the field of structural variant analysis.