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Related Experiment Videos

Constructing linkage maps in the genomics era with MapDisto 2.0.

Christopher Heffelfinger1, Christopher A Fragoso1, Mathias Lorieux2,3

  • 1Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT, USA.

Bioinformatics (Oxford, England)
|April 4, 2017
PubMed
Summary

MapDisto v.2.0 is a new, user-friendly software for geneticists to analyze large genotyping by sequencing (GBS) datasets and construct genetic linkage maps efficiently on desktop computers.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genotyping by sequencing (GBS) produces large datasets.
  • Current genetic mapping software struggles with GBS data size and efficiency.
  • There is a need for user-friendly, efficient desktop software for GBS data analysis.

Purpose of the Study:

  • To develop and present MapDisto v.2.0, a new software for genetic linkage map construction.
  • To address the computational challenges posed by large GBS datasets.
  • To provide geneticists with a user-friendly tool for analyzing GBS data.

Main Methods:

  • MapDisto v.2.0 incorporates new Java modules for efficient data handling.
  • The software supports direct importation and conversion of Variant Call Format (VCF) files.

Related Experiment Videos

  • It includes novel methods for linkage detection, data imputation (LB-Impute), and quantitative trait loci (QTL) detection via R/qtl.

    • Main Results:

    • MapDisto v.2.0 efficiently handles very large GBS datasets.
    • The software enables direct VCF file processing and conversion.
    • New features include linkage detection, LB-Impute for VCF data imputation, and R/qtl integration for QTL detection.

    Conclusions:

    • MapDisto v.2.0 offers a user-friendly solution for geneticists analyzing large GBS datasets.
    • The software improves computational efficiency in terms of speed and memory usage.
    • MapDisto v.2.0 facilitates genetic linkage map construction and QTL analysis.