Literature DB >> 22301650

Genetic analysis: moving between linkage and association.

Albert Vernon Smith.   

Abstract

The approaches to identifying genes and genomic regions associated with human disease can be grouped into two categories: linkage analysis and genetic association analysis. Linkage analysis is useful for diseases of high penetrance that run strongly within families, but is limited in its ability to detect situations where there are multiple genes with smaller effects. An alternative is genetic association studies, which were initially performed on small numbers of candidate genes. This approach identified relatively few genes that were consistently associated with disease, but it is now possible to do a genetic association for the whole genome, making this approach more powerful. In practice, the two types of analysis are often interlinked. This article provides information on the tools needed to perform both genetic linkage and genetic association analysis.

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Year:  2012        PMID: 22301650     DOI: 10.1101/pdb.top067819

Source DB:  PubMed          Journal:  Cold Spring Harb Protoc        ISSN: 1559-6095


  4 in total

Review 1.  Dissecting Complex and Multifactorial Nature of Alzheimer's Disease Pathogenesis: a Clinical, Genomic, and Systems Biology Perspective.

Authors:  Puneet Talwar; Juhi Sinha; Sandeep Grover; Chitra Rawat; Suman Kushwaha; Rachna Agarwal; Vibha Taneja; Ritushree Kukreti
Journal:  Mol Neurobiol       Date:  2015-09-09       Impact factor: 5.590

2.  A multiple regression method for genomewide association studies using only linkage information.

Authors:  Bujun Mei; Zhihua Wang
Journal:  J Genet       Date:  2018-06       Impact factor: 1.166

Review 3.  Multifaceted Alzheimer's Disease: Building a Roadmap for Advancement of Novel Therapies.

Authors:  Dapinder Kaur; Tapan Behl; Aayush Sehgal; Sukhbir Singh; Neelam Sharma; Simona Bungau
Journal:  Neurochem Res       Date:  2021-08-06       Impact factor: 3.996

4.  Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease.

Authors:  Puneet Talwar; Yumnam Silla; Sandeep Grover; Meenal Gupta; Rachna Agarwal; Suman Kushwaha; Ritushree Kukreti
Journal:  BMC Genomics       Date:  2014-03-15       Impact factor: 3.969

  4 in total

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