pQTL Mediation analysis

Description Usage Arguments See Also Examples

For a given QTL haplotype probabilities driver and target target, the function sequentially tries to add each column m of mediator matrix as a covariate and calculates LOD statistic. The low LOD value indicates driver and target are conditionally independent given m, i.e. m is a mediator of causal relationship from driver to target.

1
2
3

mediator_lod(mediator, driver, annotation, covar_med = NULL,
  intcovar = NULL, kinship = NULL, facet_name = "chr",
  index_name = "pos", verbose = TRUE)

`mediator`	A matrix, each column is one gene/protein's expression
`driver`	A matrix, haplotype probabilities at QTL we try to mediate
`annotation`	A data frame with mediators' annotation with columns for 'facet_name' and 'index_name'
`covar_med`	A matrix with additive covariates
`intcovar`	A matrix of covariate interacting with driver
`kinship`	kinship object
`facet_name`	name of facet column (default 'chr')
`index_name`	name of index column (default 'pos')
`verbose`	If TRUE display information about the progress

plot.mediation, kplot

data(Tmem68)
med_lod <- mediator_lod(mediator = Tmem68$mediator,
                      driver = Tmem68$qtl.geno,
                      annotation = Tmem68$annotation,
                      covar_med = NULL)
ggplot2::autoplot(med_lod) +
  ggplot2::geom_hline(yintercept = 5, col = "blue")