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Applications of Spatio-temporal Mapping and Particle Analysis Techniques to Quantify Intracellular Ca2+ Signaling In Situ

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Composite interval mapping and multiple interval mapping: procedures and guidelines for using Windows QTL

Luciano Da Costa E Silva¹, Shengchu Wang, Zhao-Bang Zeng

¹Department of Statistics and Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA.

Methods in Molecular Biology (Clifton, N.J.)

|May 9, 2012

Summary

This summary is machine-generated.

This chapter introduces composite interval mapping and multiple interval mapping for quantitative trait loci (QTL) discovery in inbred line crosses. It provides practical guidance for using Windows QTL Cartographer for analysis and result interpretation.

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Area of Science:

Genetics
Statistical Genetics
Bioinformatics

Background:

Significant advancements in statistical methods for quantitative trait loci (QTL) mapping.
Focus on crosses derived from inbred lines.

Purpose of the Study:

Introduce composite interval mapping and multiple interval mapping methods.
Provide detailed instructions for QTL analysis using Windows QTL Cartographer.
Explain analysis options and interpretation of mapping results.

Main Methods:

Composite Interval Mapping (CIM)
Multiple Interval Mapping (MIM)
Utilizing Windows QTL Cartographer software

Main Results:

Demonstration of CIM and MIM procedures.
Explanation of software options and parameters.
Interpretation of QTL mapping results through a practical example.

Conclusions:

Empowers researchers to perform and interpret QTL mapping analyses.
Facilitates the application of advanced statistical methods in genetic studies.
Enhances understanding of genetic architecture underlying quantitative traits.