estDropoutNum {scRecover} | R Documentation

## estDropoutNum: Estimate dropout gene number in a cell

### Description

This function is used to estimate dropout gene number in a cell for single-cell RNA-seq (scRNA-seq) data. It takes a non-negative vector of scRNA-seq raw read counts of a cell as input.

### Usage

    estDropoutNum(sample = NULL, depth = 20, histCounts = NULL,
      return = "dropoutNum")

### Arguments

`sample` | A cell's raw read counts for each gene, could be a vector or a SingleCellExperiment object.
`depth` | Relative sequencing depth to be predicted compared with initial sample depth, should between 0-100, default is 20.
`histCounts` | Optional. Only needed when `sample` is blank or `sample = NULL`. A histogram table of raw read counts for the cell.
`return` | A character for choosing the return value type of the function. "dropoutNum" (default) for dropout gene number, "geneNumPredict" for all expressed gene number predicted, "transcriptNum" for all transcript number predicted.

### Value

The dropout gene number (or all expressed gene number) predicted in a cell.

### Author(s)

Zhun Miao.

### See Also

`scRecover`, for imputation of single-cell RNA-seq data.

`countsSampling`, for downsampling the read counts in a cell.

`normalization`, for normalization of single-cell RNA-seq data.

`scRecoverTest`, a test dataset for scRecover.

### Examples

    # Load test data
    data(scRecoverTest)

    # Estimate dropout gene number in a cell
    estDropoutNum(sample = counts[,1], return = "dropoutNum")

    # Estimate all expressed gene number in a cell
    estDropoutNum(sample = counts[,1], return = "geneNumPredict")

[Package scRecover version 1.4.1 Index]