Publication: Accounting for relatedness in family-based association studies: Application to Genetic Analysis Workshop 18 data
Issued Date
2014-06-17
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ISSN
17536561
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2-s2.0-85018193032
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Mahidol University
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SCOPUS
Bibliographic Citation
BMC Proceedings. Vol.8, (2014)
Suggested Citation
Jakris Eu-Ahsunthornwattana, Richard Aj Howey, Heather J. Cordell Accounting for relatedness in family-based association studies: Application to Genetic Analysis Workshop 18 data. BMC Proceedings. Vol.8, (2014). doi:10.1186/1753-6561-8-S1-S79 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/33251
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Title
Accounting for relatedness in family-based association studies: Application to Genetic Analysis Workshop 18 data
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Abstract
© 2014 Eu-ahsunthornwattana et al.; licensee BioMed Central Ltd. In the last few years, a bewildering variety of methods/software packages that use linear mixed models to account for sample relatedness on the basis of genome-wide genomic information have been proposed. We compared these approaches as implemented in the programs EMMAX, FaST-LMM, Gemma, and GenABEL (FASTA/GRAMMAR-Gamma) on the Genetic Analysis Workshop 18 data. All methods performed quite similarly and were successful in reducing the genomic control inflation factor to reasonable levels, particularly when the mean values of the observations were used, although more variation was observed when data from each time point were used individually. From a practical point of view, we conclude that it makes little difference to the results which method/software package is used, and the user can make the choice of package on the basis of personal taste or computational speed/convenience.