From 95c169cf6d1b8e63ddc0665082d7f00f18d95f93 Mon Sep 17 00:00:00 2001 From: shawinke Date: Fri, 27 Mar 2020 11:50:54 +0100 Subject: [PATCH] Reducing data size --- DESCRIPTION | 2 +- NAMESPACE | 2 +- R/SPsimSeq.R | 11 ++++------ R/configExperiment.R | 2 -- R/dSPsimSeq.R | 45 ---------------------------------------- README.Rmd | 2 +- README.md | 2 -- data/scNGP.data.rda | Bin 1422542 -> 2041634 bytes data/zhang.data.sub.rda | Bin 1631858 -> 689031 bytes man/SPsimSeq.Rd | 11 ++++------ man/configExperiment.Rd | 2 -- man/dSPsimSeq.Rd | 42 ------------------------------------- vignettes/SPsimSeq.Rmd | 19 ++++++++--------- 13 files changed, 20 insertions(+), 120 deletions(-) delete mode 100644 R/dSPsimSeq.R delete mode 100644 man/dSPsimSeq.Rd diff --git a/DESCRIPTION b/DESCRIPTION index 3b860c5..b13f612 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -39,7 +39,7 @@ Imports: WGCNA, limma, mvtnorm, - phyloseq , + phyloseq, utils biocViews: GeneExpression, RNASeq, SingleCell, Sequencing, DNASeq RoxygenNote: 6.1.1 diff --git a/NAMESPACE b/NAMESPACE index 8d825f4..ed352fa 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -2,7 +2,7 @@ export(SPsimSeq) export(configExperiment) -export(dSPsimSeq) +export(evaluateDensities) import(methods) importFrom(Hmisc,cut2) importFrom(SingleCellExperiment,SingleCellExperiment) diff --git a/R/SPsimSeq.R b/R/SPsimSeq.R index fb1fb11..e34e71f 100644 --- a/R/SPsimSeq.R +++ b/R/SPsimSeq.R @@ -83,7 +83,7 @@ #' data("zhang.data.sub") #' #' # filter genes with sufficient expression (important step to avoid bugs) -#' zhang.counts <- zhang.data.sub$counts[rowSums(zhang.data.sub$counts > 0)>=5, ] +#' zhang.counts <- zhang.data.sub$counts #' MYCN.status <- zhang.data.sub$MYCN.status #' #' # We simulate only a single data (n.sim = 1) with the following property @@ -100,13 +100,11 @@ #' #' # simulate data #' set.seed(6452) -#' zhang.counts2 <- zhang.counts[sample(nrow(zhang.counts), 2000), ] #' sim.data.bulk <- SPsimSeq(n.sim = 1, s.data = zhang.counts2, #' group = MYCN.status, n.genes = 2000, batch.config = 1, #' group.config = c(0.5, 0.5), tot.samples = 20, #' pDE = 0.1, lfc.thrld = 0.5, result.format = "list") #' -#' #' head(sim.data.bulk$counts[[1]][, seq_len(5)]) # count data #' head(sim.data.bulk$colData) # sample info #' head(sim.data.bulk$rowData) # gene info @@ -131,14 +129,13 @@ #' data("scNGP.data") #' #' # filter genes with sufficient expression (important step to avoid bugs) -#' scNGP.data2 <- scNGP.data[rowSums(counts(scNGP.data) > 0)>=5, ] -#' treatment <- ifelse(scNGP.data2$characteristics..treatment=="nutlin",2,1) +#' treatment <- ifelse(scNGP.data$characteristics..treatment=="nutlin",2,1) #' #' set.seed(654321) -#' scNGP.data2 <- scNGP.data2[sample(nrow(scNGP.data2), 2000), ] +#' scNGP.data <- scNGP.data[sample(nrow(scNGP.data), 2000), ] #' #' # simulate data (we simulate here only a single data, n.sim = 1) -#' sim.data.sc <- SPsimSeq(n.sim = 1, s.data = scNGP.data2, group = treatment, +#' sim.data.sc <- SPsimSeq(n.sim = 1, s.data = scNGP.data, group = treatment, #' n.genes = 2000, batch.config = 1, #' group.config = c(0.5, 0.5), tot.samples = 100, #' pDE = 0.1, lfc.thrld = 0.5, model.zero.prob = TRUE, diff --git a/R/configExperiment.R b/R/configExperiment.R index 114bb9d..3feb295 100644 --- a/R/configExperiment.R +++ b/R/configExperiment.R @@ -12,7 +12,6 @@ #' and the experiment configurartion #' @export #' @examples -#' \donttest{ #' batch = sample(LETTERS[1:3], 20, replace = TRUE) #' group = sample(1:3, 20, replace = TRUE) #' #---- a design with a total of 10 samples/cells from 1 batch and 1 group @@ -34,7 +33,6 @@ #' # respectively. #' configExperiment(batch.config = c(5/30, 10/30, 15/30), group.config = c(0.5, 0.5), #' tot.samples = 30, batch = batch, group = group) -#' } configExperiment <- function(batch.config, group.config, tot.samples, batch, group){ #Sort, such that largest groups and largest batches match with simulation batch.config = sort(batch.config, decreasing = TRUE) diff --git a/R/dSPsimSeq.R b/R/dSPsimSeq.R deleted file mode 100644 index 4ad6179..0000000 --- a/R/dSPsimSeq.R +++ /dev/null @@ -1,45 +0,0 @@ -#' Evaluate the densities in the estimated SPsimSeq object -#' @param SPobj The SPsimSeq object, with details retained -#' @param newData A character vector of gene names -#' @return a list of estimated densities, breaks and midpoints, one for every -#' gene in newData -#' @export -#' @examples -#' data("zhang.data.sub") -#' # filter genes with sufficient expression (important step to avoid bugs) -#' zhang.counts <- zhang.data.sub$counts[rowSums(zhang.data.sub$counts > 0)>=5, ] -#' MYCN.status <- zhang.data.sub$MYCN.status -#' # simulate data -#' zhang.counts2 <- zhang.counts[sample(nrow(zhang.counts), 2000), ] -#' sim.data.bulk <- SPsimSeq(n.sim = 1, s.data = zhang.counts2, -#' group = MYCN.status, n.genes = 2000, batch.config = 1, -#' group.config = c(0.5, 0.5), tot.samples = 20, -#' pDE = 0.1, lfc.thrld = 0.5, result.format = "list", -#' return.details = TRUE) -#' outDens = dSPsimSeq(sim.data.bulk) -#' select.genes <- sample(names(outDens), 4) -#' select.sample = sample( -#' seq_along(sim.data.bulk$detailed.results$exprmt.design$sub.groups), 1) -#' par(mfrow=c(2, 2)) -#' for(i in select.genes){ -#' plot(outDens[[i]][[select.sample]]$mids, outDens[[i]][[select.sample]]$gy, type = "l", -#' xlab = "Outcome", ylab = "Density", main = paste("Gene", i)) -#' } -dSPsimSeq <- function(SPobj, newData = names(SPobj$detailed.results$densList)){ - if(!"detailed.results" %in% names(SPobj)){ - stop("Estimated densities needed, try running SPsimSeq with - return.details = TRUE") - } - if(!is.character(newData)){ - stop("Provide a character vector of genes") - } - dets = SPobj$detailed.results #details - names(newData) = newData - #Construct the appropriate densities - lapply(newData, function(gene){ - constructDens(returnDens = TRUE, - DE.ind.ii = gene %in% dets$cand.DE.genes$nonnull.genes, - exprmt.design = dets$exprmt.design, - densList.ii = dets$densList[[gene]]) - }) -} \ No newline at end of file diff --git a/README.Rmd b/README.Rmd index 62b0e18..5de47d6 100644 --- a/README.Rmd +++ b/README.Rmd @@ -21,7 +21,7 @@ BioConductor installation ```{r biocinstall, eval = FALSE} library(BiocManager) -BiocManager::install("SPsimSeq", update = FALSE) +BiocManager::install("SPsimSeq") ``` ```{r loadspsimseqpackage} diff --git a/README.md b/README.md index f383ece..b40781d 100644 --- a/README.md +++ b/README.md @@ -68,8 +68,6 @@ sim.data.bulk <- SPsimSeq(n.sim = 1, s.data = zhang.counts2, ## Estimating featurewise correlations ... - ## - ## Selecting candidate DE genes ... ## Note: The number of DE genes detected in the source data is 79 and the number of DE genes required to be included in the simulated data is 200. 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