differentialExpression {celda} | R Documentation

## Differential expression for cell subpopulations using MAST

### Description

Uses MAST to find differentially expressed features for specified cell subpopulations.

### Usage

    differentialExpression(x, ...)

    ## S4 method for signature 'SingleCellExperiment'
    differentialExpression(
      x,
      useAssay = "counts",
      altExpName = "featureSubset",
      c1,
      c2 = NULL,
      onlyPos = FALSE,
      log2fcThreshold = NULL,
      fdrThreshold = 1
    )

    ## S4 method for signature 'matrix'
    differentialExpression(
      x,
      celdaMod,
      c1,
      c2 = NULL,
      onlyPos = FALSE,
      log2fcThreshold = NULL,
      fdrThreshold = 1
    )

### Arguments

`x` | A numeric matrix of counts or a SingleCellExperiment with the matrix located in the assay slot under `useAssay`. Rows represent features and columns represent cells. Must contain cluster labels in `celdaClusters(x, altExpName = altExpName)` if `x` is a SingleCellExperiment object.
`...` | Ignored. Placeholder to prevent check warning.
`useAssay` | A string specifying which assay slot to use if `x` is a SingleCellExperiment object. Default "counts".
`altExpName` | The name for the altExp slot to use. Default "featureSubset".
`c1` | Integer vector. Cell populations to include in group 1 for the differential expression analysis.
`c2` | Integer vector. Cell populations to include in group 2 for the differential expression analysis. If NULL, the clusters in the c1 group are compared to all other clusters. Default NULL.
`onlyPos` | Logical. Whether to only return markers with positive log2 fold change. Default FALSE.
`log2fcThreshold` | Numeric. A number greater than 0 that specifies the absolute log2 fold change threshold. Only features with absolute value above this threshold will be returned. If NULL, this filter will not be applied. Default NULL.
`fdrThreshold` | Numeric. A number between 0 and 1 that specifies the false discovery rate (FDR) threshold. Only features below this threshold will be returned. Default 1.
`celdaMod` | Celda object of class 'celda_C' or 'celda_CG'.

### Value

Data frame containing MAST results including statistics such as p-value, log2 fold change, and FDR.

### Examples

    data(sceCeldaCG)
    clusterDiffexpRes <- differentialExpression(sceCeldaCG, c1 = c(1, 2))
    data(celdaCGSim, celdaCGMod)
    clusterDiffexpRes <- differentialExpression(celdaCGSim$counts,
      celdaCGMod,
      c1 = c(1, 2))

[Package celda version 1.6.1 Index]