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Meander: visually exploring the structural variome using space-filling curves.

Georgios A Pavlopoulos1, Parveen Kumar, Alejandro Sifrim

  • 1Department of Electrical Engineering (ESAT/SCD), University of Leuven, Kasteelpark Arenberg 10, Box 2446, 3001 Leuven, Belgium. g.pavlopoulos@med.uoc.gr

Nucleic Acids Research
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Summary
This summary is machine-generated.

New software visualizes structural variations (SVs) in genomes. This tool enables direct comparison of multiple individuals, advancing genome-wide studies beyond single gene analysis.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing enables genome-wide studies, shifting focus from single genes to entire genomes.
  • Current methods for identifying and visualizing structural variations (SVs) are less developed than those for single nucleotide polymorphisms.
  • Existing genome browsers primarily compare a single sequence to a reference, limiting direct multi-individual comparisons.

Purpose of the Study:

  • To develop an efficient approach for exploring and visualizing structural variations (SVs).
  • To enable direct comparison of multiple individuals' genomes for SV analysis.
  • To introduce a novel visualization method for structural variations.

Main Methods:

  • Utilized space-filling Hilbert curves for SV exploration.
  • Incorporated both read-depth and pair-end sequencing information.
  • Developed an interactive, open-source Java application named Meander.

Main Results:

  • Meander allows users to explore SVs at various resolutions.
  • The application facilitates simultaneous comparison of up to four individuals against a reference genome.
  • Functionality demonstrated through two case studies.

Conclusions:

  • The developed visualization approach effectively addresses the challenge of comparing multiple individuals for SVs.
  • Meander provides an efficient and interactive tool for genome-wide structural variation analysis.
  • This method enhances the exploration and visualization of complex genomic variations.