cape (version 2.0.2)

pairscan.noKin: Performs a pairscan without a kinship correction.

Description

This function performs the pairwise regression on all selected marker pairs. The phenotypes used can be either eigentraits or raw phenotypes.

Usage

pairscan.noKin(data.obj, pheno.mat, geno.mat, 
covar.table, paired.markers, n.perm, verbose,
n.cores = NULL)

Arguments

data.obj

The object in which all results are stored. See read.population.

pheno.mat

A matrix holding the phenotypes in columns and individuals in rows

geno.mat

A matrix of genotype values with markers in columns and individuals in rows. Elements indicate the probability of an alternate allele at each marker for each individual.

covar.table

A matrix holding values for covariates in columns and individuals in rows.

paired.markers

A two-column matrix indicating which marker pairs to test in the pairscan.

n.perm

The number of total permutations to be performed.

verbose

A logical value indicating whether the progress of the scan should be printed to the screen.

n.cores

An integer specifying the number of cores to be used in parallel processing. If NULL, the choice is made automatically.

Value

This function adds an element to the pairscan object reporting the results of the pair-wise scan:

pairscan.effects

A matrix with five columns indicating the names of markers 1 and 2, their effect sizes, and the effect size of their interaction

pairscan.se

A table of the standard errors from the test on each marker pair. The columns are identical to those described for pairscan.effects

model.covariance

This is a table in which each row is the linearized matrix of the variance-covariance matrix of each pairwise regression.

References

Carter, G. W., Hays, M., Sherman, A., & Galitski, T. (2012). Use of pleiotropy to model genetic interactions in a population. PLoS genetics, 8(10), e1003010. doi:10.1371/journal.pgen.1003010

See Also

pairscan, pairscan.kin