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MUGBAS: a species free gene-based programme suite for post-GWAS analysis.

S Capomaccio1, M Milanesi1, L Bomba1

  • 1Istituto di Zootecnica, Università Cattolica del Sacro Cuore, 29122, Piacenza, Italy.

Bioinformatics (Oxford, England)
|March 14, 2015
PubMed
Summary

This study introduces MUGBAS, a new software tool for gene-based association analysis in diverse species. MUGBAS enables researchers to estimate gene association P-values using genomic data, advancing genetic studies beyond humans.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-Wide Association Studies (GWAS) are crucial for linking molecular markers to phenotypes in various species.
  • Existing tools for gene-based association analysis are primarily limited to human studies.
  • A need exists for versatile software applicable across multiple species.

Purpose of the Study:

  • To introduce MUGBAS (MUlti species Gene-Based Association Suite), a novel software for gene-based association analysis.
  • To provide a tool that estimates gene-level P-values from single-marker GWAS results.
  • To develop a species- and annotation-independent solution for genetic association studies.

Main Methods:

  • MUGBAS utilizes single marker GWAS results, genotype data, and gene annotation information.
  • The software is designed for high-density marker studies and is highly parallelized for speed.
  • It is species- and annotation-independent, allowing broad applicability.

Main Results:

  • MUGBAS successfully estimates gene-based association P-values.
  • The software demonstrates efficiency and parallelization capabilities.
  • It is ready for application in high-density marker studies across various species.

Conclusions:

  • MUGBAS offers a valuable, versatile tool for gene-based association studies in both model and non-model species.
  • The software addresses a gap in current bioinformatics tools for cross-species genetic analysis.
  • MUGBAS facilitates a deeper understanding of the genetic architecture of traits.