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A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

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Computational approaches and software tools for genetic linkage map estimation in plants.

Jitender Cheema¹, Jo Dicks

¹John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UH, UK.

Briefings in Bioinformatics

|November 26, 2009

Summary

This review introduces computational approaches and software tools for estimating plant genetic maps. It aims to help plant geneticists and bioinformaticians understand complex mapping challenges and available solutions for crop improvement.

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Area of Science:

Plant genetics
Bioinformatics
Computational biology

Background:

Genetic maps are crucial for crop plant improvement.
Estimating genetic maps is computationally complex, especially with high-throughput DNA markers.
Bioinformaticians face challenges in developing scalable and user-friendly mapping software.

Purpose of the Study:

To provide an overview of computational approaches for plant genetic map estimation.
To introduce software tools that implement these computational methods.
To bridge the knowledge gap between plant geneticists and bioinformaticians in this field.

Main Methods:

Discussion of key computational concepts in genetic map estimation.
Review of various software tools designed for genetic mapping.
Focus on methods that handle large datasets and incorporate expert knowledge.

Main Results:

A survey of computational strategies for genetic map construction.
Identification of software solutions for different dataset sizes and complexities.
Emphasis on user-friendly tools for plant geneticists.

Conclusions:

Computational approaches are essential for modern plant genetic map estimation.
Accessible software tools facilitate the use of genetic maps in crop improvement.
This review serves as an introduction for both geneticists and bioinformaticians.