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FunMap: functional mapping of complex traits.

Chang-Xing Ma1, Rongling Wu, George Casella

  • 1Department of Statistics, 533 McCarty Hall C, University of Florida, Gainesville, FL 32611, USA. cma@biostat.ufl.edu

Bioinformatics (Oxford, England)
|February 28, 2004
PubMed
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FunMap software maps quantitative trait loci (QTL) for function-valued traits in populations. It visualizes dynamic QTL effects over time, aiding genetic studies of growth and development.

Area of Science:

  • Genetics
  • Bioinformatics
  • Developmental Biology

Background:

  • Quantitative trait loci (QTL) analysis is crucial for understanding complex traits.
  • Function-valued traits, or infinite-dimensional traits, present unique analytical challenges.
  • Existing software may not adequately address the mapping of QTL for dynamic, time-course data.

Purpose of the Study:

  • To introduce FunMap, a novel Web-based interface for QTL mapping.
  • To enable the analysis of function-valued traits in various population structures.
  • To facilitate the investigation of dynamic changes in QTL effects.

Main Methods:

  • FunMap utilizes user-provided longitudinal trait data, marker genotypes, and linkage maps.
  • The software performs systematic genome-wide scans to identify QTL.

Related Experiment Videos

  • It includes significance testing for identified QTL across the entire map.

    • Main Results:

    • FunMap successfully maps QTL for function-valued traits.
    • The software automatically generates visualizations of dynamic QTL effects over time.
    • It allows for the testing of specific biological hypotheses related to genetic control.

    Conclusions:

    • FunMap provides a powerful tool for dissecting the genetic architecture of growth and development.
    • The software enhances the study of complex traits by accommodating longitudinal data.
    • It offers a user-friendly interface for advanced QTL analysis in genetics research.