Linkage Disequilibrium and Association Mapping (eBook, PDF)

Analysis and Applications
Redaktion: Collins, Andrew R.

• Format: PDF

Produktbeschreibung

As researchers continue to make enormous progress in mapping disease genes, exciting, novel, and complex analyses have emerged. In Linkage Disequilibrium and Association Mapping: Analysis and Applications, scientists from around the world, who are leaders in this field, contribute their vast experience and expertise to produce a comprehensive and fascinating text for researchers and clinicians alike.

The volume comprises four general sections: the first presents an overview and historical basis of the subject. The second section considers the developing methodology and recent findings from studies which have characterized the genome-wide linkage disequilibrium structure in enormous detail. The following section examines all aspects of disease association mapping methodology, and the final two chapters review the early successes in mapping genes involved in two of the most important human diseases: asthma and type 2 diabetes.

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Produktdetails

• Verlag: Humana Press
• Seitenzahl: 255
• Erscheinungstermin: 5. Februar 2008
• Englisch
• ISBN-13: 9781597453899
• Artikelnr.: 64701455

Inhaltsangabe

Linkage Disequilibrium and Association Mapping.- A History of Association Mapping.- Linkage Disequilibrium Maps and Location Databases.- LDMAP.- Linkage Disequilibrium as a Tool for Detecting Signatures of Natural Selection.- The Genetic Basis of Complex Traits.- Linkage Disequilibrium Mapping for Complex Disease Genes.- Linkage Disequilibrium Maps and Disease-Association Mapping.- Coalescent Methods for Fine-Scale Disease-Gene Mapping.- Family-Based Linkage Disequilibrium Tests Using General Pedigrees.- Association Studies Using Familial Cases.- Association Mapping Using Pooled DNA.- Selecting Single-Nucleotide Polymorphisms for Association Studies With SNPbrowser(TM) Software.- Avoiding False Discoveries in Association Studies.- Gene Mapping in Asthma-Related Traits.- Identifying Susceptibility Variants for Type 2 Diabetes.