R/DownsampleMatrix.R
downSampleDepth.Rd
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
)
SingleCellExperiment object storing all assay data from the shiny app.
Character. The name of the assay to be used for subsampling.
Numeric. The minimum number of reads found for a gene to be considered detected.
Numeric. The minimum number of cells a gene must have at least 1 read in for it to be considered detected.
Numeric. The highest number of total reads to be simulated.
Character. The name of the condition of interest. Must match a name from sample data.
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.
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[seq(1000),]
res <- downSampleDepth(subset,
realLabels = "level1class",
iterations=2)
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to min; returning Inf