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Family-based association analysis: a fast and efficient method of multivariate association analysis with multiple variants

Cited 8 time in Web of Science Cited 8 time in Scopus
Authors

Won, Sungho; Kim, Wonji; Lee, Sungyoung; Lee, Young; Sung, Joohon; Park, Taesung

Issue Date
2015-02-15
Publisher
BioMed Central
Citation
BMC Bioinformatics, 16(1):46
Keywords
Family-based association analysisMultiple variantsMultiple phenotypes
Description
This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited.
Abstract
Abstract

Background
Many disease phenotypes are outcomes of the complicated interplay between multiple genes, and multiple phenotypes are affected by a single or multiple genotypes. Therefore, joint analysis of multiple phenotypes and multiple markers has been considered as an efficient strategy for genome-wide association analysis, and in this work we propose an omnibus family-based association test for the joint analysis of multiple genotypes and multiple phenotypes.


Results
The proposed test can be applied for both quantitative and dichotomous phenotypes, and it is robust under the presence of population substructure, as long as large-scale genomic data is available. Using simulated data, we showed that our method is statistically more efficient than the existing methods, and the practical relevance is illustrated by application of the approach to obesity-related phenotypes.


Conclusions
The proposed method may be more statistically efficient than the existing methods. The application was developed in C++ and is available at the following URL:
http://healthstat.snu.ac.kr/software/mfqls/

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Language
English
URI
https://hdl.handle.net/10371/100436
DOI
https://doi.org/10.1186/s12859-015-0484-5
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