overlapExprs {scran} | R Documentation

## Overlap expression profiles

### Description

Compute the gene-specific overlap in expression profiles between two groups of cells.

This is deprecated in favor of calling `findMarkers` with `type="wilcox"`.

### Usage

    ## S4 method for signature 'ANY'
    overlapExprs(x, groups, gene.names=rownames(x), block=NULL,
        pval.type=c("any", "some", "all"), direction=c("any", "up", "down"), tol=1e-8,
        log.p=FALSE, full.stats=FALSE, subset.row=NULL, BPPARAM=SerialParam())

    ## S4 method for signature 'SingleCellExperiment'
    overlapExprs(x, ..., subset.row=NULL, assay.type="logcounts",
        get.spikes=FALSE)

### Arguments

`x` | A numeric matrix of expression values, where each column corresponds to a cell and each row corresponds to an endogenous gene. Alternatively, a SingleCellExperiment object containing such a matrix.
`groups` | A vector of group assignments for all cells.
`gene.names` | A character vector of gene names with one value for each row of `x`.
`block` | A factor specifying the blocking level for each cell.
`pval.type` | A string specifying the type of combined p-value to be computed, i.e., Simes' or IUT.
`direction` | A string specifying which direction of change in expression should be used to rank genes in the output.
`tol` | A numeric scalar specifying the tolerance with which ties are considered.
`log.p` | A logical scalar indicating if log-transformed p-values/FDRs should be returned.
`full.stats` | A logical scalar indicating whether all statistics (i.e., raw and BH-adjusted p-values) should be returned for each pairwise comparison.
`subset.row` | See `?"scran-gene-selection"`.
`BPPARAM` | A BiocParallelParam object to use in `bplapply` for parallel processing.
`...` | Additional arguments to pass to the matrix method.
`assay.type` | A string specifying which assay values to use, e.g., `"counts"` or `"logcounts"`.
`get.spikes` | See `?"scran-gene-selection"`.

### Details

This function provides a convenience wrapper for marker gene identification, based on running `pairwiseWilcox` and passing the result to `combineMarkers`. All of the arguments above are supplied directly to one of these two functions.

Note that `log.p` only affects the combined p-values and FDRs. If `full.stats=TRUE`, the p-values for each pairwise comparison will be log-transformed regardless of the value of `log.p`.

### Value

A named list of DataFrames, each of which contains a sorted marker gene list for the corresponding cluster. See `?combineMarkers` for more details on the output format.

### See Also

See `pairwiseWilcox` and `combineMarkers` for the component functions.

See `findMarkers` for the equivalent function using t-tests.

### Examples

    # Using the mocked-up data 'y2' from this example.
    example(computeSpikeFactors)
    y2 <- normalize(y2)
    groups <- sample(3, ncol(y2), replace=TRUE)
    out <- overlapExprs(y2, groups, subset.row=1:10)

[Package scran version 1.14.6 Index]