tParallel: tParallel
In BenjaminChittick/BenCScore: Methods For Analysis of High-Throughput Screens

This function runs tContrast sampling in parallel

1 2	tParallel(data, mu.prior, var.prior, nu.prior, a, b, null.post, ROPE, alternative, runjags.method = "simple")

`data`	compound activity data with individual compounds in rows and replicates in columns
`mu.prior`	location parameter for prior distribution of mu. Typically the average of all compound activity.
`var.prior`	spread parameter for prior distribution of mu. Typically the square standard error of the mean for all compounds.
`a`	alpha parameter for prior distribution of compound variance. See EstimateAB.
`b`	beta parameter for prior distribution of compound variance. See EstimateAB.
`null.post`	a MCMC sampling of a null posterior with column name mu.
`alternative`	a character string specifying the relationship to the null posterior, must be one of "two.sided", "greater", or "less".
`runjags.method`	method by which jags is run, default is set to 'simple' to avoid conflict with snow library
`rope`	Region of Practical Equivalence. This value specifies how close the sampled posterior needs to be to the null posterior to consider them equivalent, default value is 0.

set.seed(7)
compounds <- matrix(rnorm(20, seq(0, 100, 10), 3), nrow=10)
null.reference <- rnorm(32, 0, 3)
pooled <- c(null.reference, sapply(compounds, function(x) x))
mu.prior <- median(pooled)
var.prior <- var(null.reference)
nu.prior <- 1
a <- 30
b <- 3100
ROPE <- 15

null.post <- tSample(null.reference, mu.prior, var.prior, nu.prior, a, b)
posteriors <- tParallel(compounds, mu.prior, var.prior, nu.prior, a, b,
                        null.post, ROPE, alternative='greater')
rbindlist(posteriors)
compounds