pQTL Mediation analysis

Description Usage Arguments Value Examples

Develop mediation models from driver, target and mediator

## S3 method for class 'mediation_test'
plot(x, ...)

## S3 method for class 'mediation_test'
autoplot(x, ...)

ggplot_mediation_test(x, type = c("pos_lod", "pos_pvalue", "pvalue_lod",
  "alleles", "mediator"), main = params$target, maxPvalue = 0.1,
  local_only = FALSE, significant = TRUE, lod = TRUE,
  target_index = NULL, ...)

mediation_test(target, mediator, driver, annotation = NULL,
  covar_tar = NULL, covar_med = NULL, kinship = NULL,
  driver_med = NULL, intcovar = NULL, test = c("wilcoxon",
  "binomial", "joint", "normal"), fitFunction = fitDefault,
  facet_name = "chr", index_name = "pos", ...)

`...`	additional parameters
`target`	vector or 1-column matrix with target values
`mediator`	matrix of mediators
`driver`	vector or matrix with driver values
`annotation`	A data frame with mediators' annotation with columns for 'facet_name' and 'index_name'
`covar_tar`	optional covariates for target
`covar_med`	optional covariates for mediator
`kinship`	optional kinship matrix among individuals
`driver_med`	optional driver matrix for mediators
`intcovar`	optional interactive covariates (assumed same for 'mediator' and 'target')
`test`	Type of CMST test.
`fitFunction`	function to fit models with driver, target and mediator
`facet_name`	name of facet column (default 'chr')
`index_name`	name of index column (default 'pos')

List with elements: - best best fit table - test causal test results in table - driver list of driver names for target and mediator(s) - normF Frobenius norm if using both target and mediator drivers - params list of parameter settings for use by summary and plot methods

data(Tmem68)
 
target <- Tmem68$target

# Reconstruct 8-allele genotype probabilities.
driver <- cbind(A = 1 - apply(Tmem68$qtl.geno, 1, sum), Tmem68$qtl.geno)
rownames(driver) <- rownames(Tmem68$qtl.geno)

# Find mediators with significant effect
med_lod <- mediator_lod(mediator = Tmem68$mediator,
                        driver = driver,
                        annotation = Tmem68$annotation,
                        covar_med = Tmem68$covar)
med_signif <- med_lod$id[med_lod$lod >= 5]
# Add info column.
med_lod$info <- paste("chr =", med_lod$chr)

med_test <- mediation_test(target = target,
                      mediator = Tmem68$mediator[, med_signif, drop = FALSE],
                      driver = driver,
                      annotation = med_lod,
                      covar_tar = Tmem68$covar,
                      covar_med = Tmem68$covar)
summary(med_test)
ggplot2::autoplot(med_test)