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

Description

This function runs tContrast sampling in parallel

Usage

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

Arguments

 `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.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```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 ```

BenjaminChittick/BenCScore documentation built on May 5, 2019, 2:41 p.m.