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Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

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SPAGHETTI: simulation software to test genetic mapping programs.

Nicholas A Tinker¹

¹Agriculture and Agri-Food Canada, Eastern Cereal and Oilseed Research Centre, Building 20, Central Experimental Farm, 960 Carling Avenue, Ottawa, Ontario K1A 0C6, Canada. nick.tinker@agr.gc.ca

The Journal of Heredity

|December 5, 2009

Summary

This summary is machine-generated.

SPAGHETTI simulates genetic populations with molecular markers, accounting for real-world complexities like duplicated loci and segregation distortion. This program aids in constructing and testing genetic linkage maps, with free access to its code and resources.

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Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Genetic linkage mapping is crucial for understanding genome organization and inheritance.
Simulating complex genetic scenarios is essential for developing robust mapping methodologies.
Existing simulation tools may not fully capture real-world genetic complications.

Purpose of the Study:

To introduce SPAGHETTI, a novel computer program for simulating genetic populations.
To provide a tool that incorporates realistic genetic complications into simulations.
To facilitate the development and validation of genetic linkage map construction methods.

Main Methods:

Developed a computer program named SPAGHETTI.
Incorporated features to simulate molecular markers influenced by duplicated loci and segregation distortion.
Ensured output compatibility with popular genetic mapping software.

Main Results:

SPAGHETTI successfully simulates genetic populations with complex, real-life factors.
The program's output is readily usable by standard genetic mapping software.
It serves as a valuable tool for demonstrating and testing linkage map construction techniques.

Conclusions:

SPAGHETTI offers a powerful and accessible platform for genetic population simulation.
The software aids researchers in understanding the impact of genetic complexities on linkage mapping.
Free availability of source code and resources promotes wider adoption and methodological advancement.