% Generated by roxygen2: do not edit by hand % Please edit documentation in R/DownsampleMatrix.R \name{downSampleDepth} \alias{downSampleDepth} \title{Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size} \usage{ downSampleDepth( originalData, useAssay = "counts", minCount = 10, minCells = 3, maxDepth = 1e+07, realLabels, depthResolution = 10, iterations = 10 ) } \arguments{ \item{originalData}{\linkS4class{SingleCellExperiment} object storing all assay data from the shiny app.} \item{useAssay}{Character. The name of the assay to be used for subsampling.} \item{minCount}{Numeric. The minimum number of reads found for a gene to be considered detected.} \item{minCells}{Numeric. The minimum number of cells a gene must have at least 1 read in for it to be considered detected.} \item{maxDepth}{Numeric. The highest number of total reads to be simulated.} \item{realLabels}{Character. The name of the condition of interest. Must match a name from sample data.} \item{depthResolution}{Numeric. How many different read depth should the script simulate? Will simulate a number of experimental designs ranging from 10 reads to maxReadDepth, with logarithmic spacing.} \item{iterations}{Numeric. How many times should each experimental design be simulated?} } \value{ A 3-dimensional array, with dimensions = c(iterations, depthResolution, 3). [,,1] contains the number of detected genes in each simulated dataset, [,,2] contains the number of significantly differentially expressed genes in each simulation, and [,,3] contains the mediansignificant effect size in each simulation. If no genes are significantly differentially expressed, the median effect size defaults to infinity. } \description{ Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size } \examples{ data("mouseBrainSubsetSCE") subset <- mouseBrainSubsetSCE[seq(1000),] res <- downSampleDepth(subset, realLabels = "level1class", iterations=2) }