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Paternity analysis in Excel.

Margarida Rocheta1, F Miguel Dionísio, Luís Fonseca

  • 1Centro de Botânica Aplicada à Agricultura, Secção de Genética, Instituto Superior de Agronomia (ISA), TU Lisbon, Portugal. rocheta@isa.utl.pt

Computer Methods and Programs in Biomedicine
|October 12, 2007
PubMed
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Paternity Analysis in Excel (PAE) is a new tool that simplifies genetic paternity analysis. It processes microsatellite data directly within Excel, streamlining parentage studies and genetic analyses.

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Microsatellite markers are crucial for high-discrimination power in paternity analysis and fingerprinting.
  • Existing software often requires complex data export/import procedures for analysis.

Purpose of the Study:

  • To introduce Paternity Analysis in Excel (PAE), a novel tool for performing paternity analysis directly within Microsoft Excel.
  • To simplify the process of analyzing microsatellite data for parentage assignment and related genetic parameters.

Main Methods:

  • PAE is developed using Excel-VBA and comprises two modules: a data filtering/reorganization module and a paternity analysis module.
  • The filtering module prepares sequencer data, while the analysis module computes paternity candidates assuming one known parent.

Related Experiment Videos

  • The tool was tested against established software like Cervus, FaMoz, and MLTR.

    • Main Results:

    • PAE enables users to input data and obtain paternity analysis results within the Excel environment, eliminating the need for external software.
    • The program successfully processes microsatellite data for paternity assignment, selfing rates, outcrossing rates, and biparental inbreeding estimation.
    • Validation against other software confirms PAE's accuracy and reliability.

    Conclusions:

    • PAE offers a user-friendly and efficient solution for genetic paternity analysis, particularly for researchers working within the Excel ecosystem.
    • The tool democratizes complex genetic analyses by integrating them into a widely accessible platform.
    • PAE is freely available for non-commercial use, promoting its adoption in research and education.