Novel Methods for Family-Based Genetic Studies

Part of the Methods in Molecular Biology book series (MIMB, volume 1793)


The recent development of microarray and sequencing technology allows identification of disease susceptibility genes. Although the genome-wide association studies (GWAS) have successfully identified many genetic markers related to human diseases, the traditional statistical methods are not powerful to detect rare genetic markers. The rare genetic markers are usually grouped together and tested at the set level. One of such methods is the sequence kernel association test (SKAT), which has been commonly used in the rare genetic marker analysis. In recent publications, SKAT has been extended to be applicable for family-based rare variant analysis. Here, I present three published statistical approaches for family-based rare variant analysis for: 1. continuous traits, 2. binary traits, and 3. multiple correlated traits.

Key words

Statistical analysis Sequence kernel association test Mixed model Rare genetic markers Gene-based analysis 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Division of Pulmonary Medicine, Allergy and Immunology; Department of Pediatrics, Children’s Hospital of Pittsburgh of UPMCUniversity of PittsburghPittsburghUSA

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