Please use this identifier to cite or link to this item:
|Title:||Accounting for relatedness in family-based association studies: Application to Genetic Analysis Workshop 18 data|
Richard Aj Howey
Heather J. Cordell
Newcastle University, United Kingdom
|Keywords:||Biochemistry, Genetics and Molecular Biology|
|Citation:||BMC Proceedings. Vol.8, (2014)|
|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.|
|Appears in Collections:||Scopus 2011-2015|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.