runMAST {singleCellTK} | R Documentation

## Perform differential expression analysis on SCE with MAST

### Description

Condition specification allows two methods: 1. Index level selection. Arguments `index1` and `index2` will be used. 2. Annotation level selection. Arguments `class`, `classGroup1` and `classGroup2` will be used.

### Usage

    runMAST(
      inSCE,
      useAssay = "logcounts",
      index1 = NULL,
      index2 = NULL,
      class = NULL,
      classGroup1 = NULL,
      classGroup2 = NULL,
      analysisName,
      groupName1,
      groupName2,
      covariates = NULL,
      onlyPos = FALSE,
      log2fcThreshold = NULL,
      fdrThreshold = 0.05,
      overwrite = FALSE,
      check_sanity = TRUE
    )

### Arguments

`inSCE` | SingleCellExperiment inherited object.
`useAssay` | character. A string specifying which assay to use for MAST Default `"logcounts"`.
`index1` | Any type of indices that can subset a SingleCellExperiment inherited object by cells. Specifies which cells are of interests. Default `NULL`.
`index2` | Any type of indices that can subset a SingleCellExperiment inherited object by cells. specifies the control group against those specified by `index1`. If `NULL` when using index specification, `index1` cells will be compared with all other cells. Default `NULL`.
`class` | A vector/factor with `ncol(inSCE)` elements, or a character scalar that specifies a column name of `colData(inSCE)`. Default `NULL`.
`classGroup1` | a vector specifying which "levels" given in `class` are of interests. Default `NULL`.
`classGroup2` | a vector specifying which "levels" given in `class` is the control group against those specified by `classGroup1`. If `NULL` when using annotation specification, `classGroup1` cells will be compared with all other cells.
`analysisName` | A character scalar naming the DEG analysis. Required
`groupName1` | A character scalar naming the group of interests. Required.
`groupName2` | A character scalar naming the control group. Required.
`covariates` | A character vector of additional covariates to use when building the model. All covariates must exist in `names(colData(inSCE))`. Default `NULL`.
`onlyPos` | Whether to only output DEG with positive log2_FC value. Default `FALSE`.
`log2fcThreshold` | Only out put DEGs with the absolute values of log2FC greater than this value. Default `0.25`
`fdrThreshold` | Only out put DEGs with FDR value less than this value. Default `0.05`
`overwrite` | A logical scalar. Whether to overwrite result if exists. Default `FALSE`.
`check_sanity` | Logical scalar. Whether to perform MAST's sanity check to see if the counts are logged. Default `TRUE`.

### Value

The input SingleCellExperiment object with `metadata(inSCE)$diffExp` updated with the results: a list named by `analysisName`, with `$groupNames` containing the naming of the two conditions, `$useAssay` storing the assay name that was used for calculation, `$select` storing the cell selection indices (logical) for each condition, `$result` storing a `data.frame` of the DEGs summary, and `$method` storing `"MAST"`.

### Examples

    data(scExample, package = "singleCellTK")
    sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
    logcounts(sce) <- log(counts(sce) + 1)
    sce <- runMAST(inSCE = sce, groupName1 = "Sample1",
     groupName2 = "Sample2", index1 = 1:20, index2 = 21:40,
     analysisName = "MAST")

[Package singleCellTK version 2.0.0 Index]