Filter markers by minor allele frequency.
Filter markers by Hardy-Weinberg equilibrium
Error propagation
Calculate the significance of direct influences of variant pairs on phenotypes
Calculate P Values for Interactions Based on Permutations
Remove phenotypes from the phenotype matrix
Estimate Errors of Regression Coefficients
Generate a matrix of consecutive pairs
Calculate a genome-wide significance threshold for the single-variant scan
genome.wide.threshold.1D.parallel
Calculate a genome-wide significance threshold for the single-variant scan using parallel computing.
Calculate eigentraits from phenotype matrix
Get the best layout matrix for a given number of panes per page.
Retrieve the genotype matrix with the covariates appended.
Bin a continuous vector into discrete values.
Combinatorial Analysis of Epistasis and Pleiotropy
Retrieve the genotype matrix.
Get marker names from marker numbers
Get marker numbers from marker names
Get information about covariates
Use column titles to retrieve column numbers
Convert the final results to a form plotted by plotNetwork plotCollapsedVarInf
Get marker values
Retrieve colors for use in plotting.
Retrieve the genotype matrix.
Calculate a genome-wide significance threshold for the single-variant scan
Get chromosome assignments for a vector of markers.
Find all markers in the genotype matrix that are linearly independent
Normalize and mean center phenotypes
Get the chromosomal coordinate of markers
Calculates linkage blocks using community detection.
Select marker pairs for pairscan based on filters
Kinship correction for genotype and phenotype.
Impute missing genotypes in measured markers.
Get the column index of markers in the genotype matrix
Mouse cross data from Reifsnyder et al. (2000)
Plot histograms of phenotypes.
Generate data.obj from pheno.obj and geno.obj
Calculate all leave-one-out or leave-two-out kinship matrices.
Used in plotting results of pair scan.
Create a covariate from a genetic marker.
Runs one singlescan
Perform regressions for all pairs of markers and all phenotypes.
Plot variant-to-variant influences
Plot phenotype values by individual.
Plot the final epistatic network
Read in and format data for analysis by cape Given a vector of elements, create a two-column matrix listing all pairs of elements
Plot the results of the singular value decomposition of the phenotype matrix
Create a covariate from a phenotype.
Performs a pairscan with kinship correction.
Perform regression analysis for one phenotype and all pairs of markers using a kinship correction.
Plot variant-to-variant influences
Read in and format data for analysis by cape
Print the progress of a function to the screen
plot the results from pairscan
Subset a cross object to include only specified chromosomes.
Divide a region into equal parts.
Plot the results of singlescan
Remove markers from the data.obj
Normalize a vector using rank normalization
Read in and format data for analysis by cape
Generate a null distribution for the pairscan.
Performs a pairscan without a kinship correction.
Run the single-variant regression for all phenotypes
Sort the genetic markers in the data.obj.
Write out a cape data object to .csv format.
select.markers.for.pairscan
A required step that filters variable and non-redundant markers for the pairscan
Write out a cape data object to .csv format.
Write the final results to a file
Plot correlations between phenotype pairs.
Plot qq plots of phenotype pairs.
Plot the results of singlescan as a heatmap
Subset a cross object to include specific individuals
Select a subset of the eigentraits for further analysis
Rotate a matrix 90 degrees clockwise
Remove individuals from the data.obj
Select phenotypes for analysis