DownsampleCells {singleCellTK} | R Documentation

## Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size

### Description

Estimate numbers of detected genes, significantly differentially expressed genes, and median significant effect size

### Usage

    DownsampleCells(originalData, useAssay = "counts", minCountDetec = 10,
      minCellsDetec = 3, minCellnum = 10, maxCellnum = 1000, realLabels,
      depthResolution = 10, iterations = 10, totalReads = 1e+06)

### Arguments

`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.
`minCountDetec` | Numeric. The minimum number of reads found for a gene to be considered detected.
`minCellsDetec` | Numeric. The minimum number of cells a gene must have at least 1 read in for it to be considered detected.
`minCellnum` | Numeric. The minimum number of virtual cells to include in the smallest simulated dataset.
`maxCellnum` | Numeric. The maximum number of virtual cells to include in the largest simulated dataset
`realLabels` | Character. The name of the condition of interest. Must match a name from sample data. If only two factors present in the corresponding colData, will default to t-test. If multiple factors, will default to ANOVA.
`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?
`totalReads` | Numeric. How many aligned reads to put in each simulated dataset.

### 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.

### Examples

    data("mouseBrainSubsetSCE")
    subset <- mouseBrainSubsetSCE[1:1000,]
    res <- DownsampleCells(subset,
                           realLabels = "level1class",
                           iterations=2)

[Package singleCellTK version 1.2.3 Index]