View source: R/DownsampleMatrix.R
DownsampleDepth | R Documentation |
Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size
DownsampleDepth( originalData, useAssay = "counts", minCount = 10, minCells = 3, maxDepth = 1e+07, realLabels, depthResolution = 10, iterations = 10 )
originalData |
SCtkExperiment. The SCtkExperiment object storing all assay data from the shiny app. |
useAssay |
Character. The name of the assay to be used for subsampling. |
minCount |
Numeric. The minimum number of reads found for a gene to be considered detected. |
minCells |
Numeric. The minimum number of cells a gene must have at least 1 read in for it to be considered detected. |
maxDepth |
Numeric. The highest number of total reads to be simulated. |
realLabels |
Character. The name of the condition of interest. Must match a name from sample data. |
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. |
iterations |
Numeric. How many times should each experimental design be simulated? |
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.
data("mouseBrainSubsetSCE") subset <- mouseBrainSubsetSCE[1:1000,] res <- DownsampleDepth(subset, realLabels = "level1class", iterations=2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.