GWAS for Multiple Observations on Related Individuals
Extracts the chromosome numbers
Computes a Genetic Relationship Matrix from a GenABEL-like object
Constructs the (co)variance matrix for y
Creates a gwaa.data2 object
Creates a scan.gwaa2 object
Function to estimate lambda
An S4 class to represent GWAS input data
Extracts the id names
A function to subset an gwaa.data2 object
Extracts the map information
Extracts the number of ids
Function to plot P-values as a Manhattan plot
Fits a linear mixed model (without fixed SNP effects) and computes the...
GWAS for Studies having Repeated Measurements on Related Individuals
An S4 class to represent SNP data
Function to simulate genotype data for the RepeatABEL package.
Simulation function for the RepeatABEL package.
Imputes column means to missing genotypes
An S4 class to represent SNP data
Extracts the snpnames
Summary function for the rGLS output
Performs genome-wide association studies (GWAS) on individuals that are both related and have repeated measurements. For each Single Nucleotide Polymorphism (SNP), it computes score statistic based p-values for a linear mixed model including random polygenic effects and a random effect for repeated measurements. The computed p-values can be visualized in a Manhattan plot. For more details see Ronnegard et al. (2016) <doi:10.1111/2041-210X.12535> and for more examples see <https://github.com/larsronn/RepeatABEL_Tutorials>.