R/configExperiment.R

In SPsimSeq: Semi-parametric simulation tool for bulk and single-cell RNA sequencing data

#' Configure experiment
#'
#' @param batch.config a numerical vector for the marginal fraction of samples in each batch.
#' The number of batches to be simulated is equal to the size of the vector.
#' All values must sum to 1.
#' @param group.config a numerical vector for the marginal fraction of samples in each group.
#' The number of groups to be simulated is equal to the size of the vector. All values must sum to 1.
#' @param tot.samples total number of samples to be simulated.
#' @param batch,group batch and grouping vectors
#'
#' @return a list object contating the number of groups and batches to be simukated,
#' and the experiment configurartion
#' @export
#' @examples
#' batch = sample(LETTERS[seq_len(3)], 20, replace = TRUE)
#' group = sample(seq_len(3), 20, replace = TRUE)
#' #---- a design with a total of 10 samples/cells from 1 batch and 1 group
#' configExperiment(batch.config=1, group.config=1, tot.samples=10,
#' batch = batch, group = group)
#'
#' #---- a design with a total of 20 samples/cells from 1 group and 2 batchs with
#' # batch 1 has 15 samples/cells and batch 2 has 5
#' configExperiment(batch.config = c(15/20, 5/20), group.config = 1,
#' tot.samples = 20, batch = batch, group = group)
#'
#' #---- a design with a total of 20 samples/cells from 1 batch and 2 groups with
#' # group 1 has 10 samples/cells and batch 2 has 10
#' configExperiment(batch.config=1, group.config=c(0.5, 0.5), tot.samples=20,
#' batch = batch, group = group)
#'
#' #---- a design with a total of 30 samples/cells from 2 groups with group 1 has 15 samples
#' # and group 2 has 15, and  three batchs with batch 1,2, and 3 have 5, 10, and 15 samples/cells,
#' # respectively.
#' configExperiment(batch.config = c(5/30, 10/30, 15/30), group.config = c(0.5, 0.5),
#'  tot.samples = 30, batch = batch, group = group)
configExperiment <- function(batch.config, group.config, tot.samples, batch, group){
  #Sort, such that largest groups and largest batches match with simulation
  batch.config = sort(batch.config, decreasing = TRUE)
  group.config = sort(group.config, decreasing = TRUE)
  #Assign names, and select most abundant groups and batches to sample from
  namesBatch = names(sort(table(batch), decreasing = TRUE))[seq_along(batch.config)]
  namesGroup = names(sort(table(group), decreasing = TRUE))[seq_along(group.config)]
  names(batch.config) <- namesBatch
  names(group.config) <- namesGroup
  #Configure the experiment
  exprmt.config <- round(tcrossprod(batch.config, group.config)*tot.samples)
  rownames(exprmt.config) <- names(batch.config)
  colnames(exprmt.config) <- names(group.config)
  sub.batchs = rep(rep(namesBatch, ncol(exprmt.config)), times = c(exprmt.config))
  sub.groups = rep(namesGroup, times = colSums(exprmt.config))
  list(exprmt.config = exprmt.config, sub.batchs = sub.batchs,
       sub.groups = sub.groups)
}