getMarkerFeatures: Identify Marker Features for each cell grouping
In haibol2016/ArchR_debug: Analyzing single-cell regulatory chromatin in R.

getMarkerFeatures

R Documentation

Identify Marker Features for each cell grouping

Description

This function will identify features that are definitional of each provided cell grouping where possible

Usage

getMarkerFeatures(
  ArchRProj = NULL,
  groupBy = "Clusters",
  useGroups = NULL,
  bgdGroups = NULL,
  useMatrix = "GeneScoreMatrix",
  bias = c("TSSEnrichment", "log10(nFrags)"),
  normBy = NULL,
  testMethod = "wilcoxon",
  maxCells = 500,
  scaleTo = 10^4,
  threads = getArchRThreads(),
  k = 100,
  bufferRatio = 0.8,
  binarize = FALSE,
  useSeqnames = NULL,
  verbose = TRUE,
  logFile = createLogFile("getMarkerFeatures")
)

Arguments

`ArchRProj`	An `ArchRProject` object.
`groupBy`	The name of the column in `cellColData` to use for grouping cells together for marker feature identification.
`useGroups`	A character vector that is used to select a subset of groups by name from the designated `groupBy` column in `cellColData`. This limits the groups used to perform marker feature identification.
`bgdGroups`	A character vector that is used to select a subset of groups by name from the designated `groupBy` column in `cellColData` to be used for background calculations in marker feature identification.
`useMatrix`	The name of the matrix to be used for performing differential analyses. Options include "GeneScoreMatrix", "PeakMatrix", etc.
`bias`	A character vector indicating the potential bias variables (i.e. c("TSSEnrichment", "log10(nFrags)")) to account for in selecting a matched null group for marker feature identification. These should be column names from `cellColData`.
`normBy`	The name of a numeric column in `cellColData` that should be normalized across cells (i.e. "ReadsInTSS") prior to performing marker feature identification.
`testMethod`	The name of the pairwise test method to use in comparing cell groupings to the null cell grouping during marker feature identification. Valid options include "wilcoxon", "ttest", and "binomial".
`maxCells`	The maximum number of cells to consider from a single-cell group when performing marker feature identification.
`scaleTo`	Each column in the matrix designated by `useMatrix` will be normalized to a column sum designated by `scaleTo`.
`threads`	The number of threads to be used for parallel computing.
`k`	The number of nearby cells to use for selecting a biased-matched background while accounting for `bgdGroups` proportions.
`bufferRatio`	When generating optimal biased-matched background groups of cells to determine significance, it can be difficult to find sufficient numbers of well-matched cells to create a background group made up of an equal number of cells. The `bufferRatio` indicates the fraction of the total cells that must be obtained when creating the biased-matched group. For example to create a biased-matched background for a group of 100 cells, when `bufferRatio` is set to 0.8 the biased-matched background group will be composed of the 80 best-matched cells. This option provides flexibility in the generation of biased-matched background groups given the stringency of also maintaining the group proportions from `bgdGroups`.
`binarize`	A boolean value indicating whether to binarize the matrix prior to differential testing. This is useful when `useMatrix` is an insertion counts-based matrix.
`useSeqnames`	A character vector that indicates which `seqnames` should be plotted in the heatmap. Features from `seqnames` that are not listed will be ignored. In the context of a `Sparse.Assays.Matrix`, such as a matrix containing chromVAR deviations, the `seqnames` do not correspond to chromosomes, rather they correspond to the sub-portions of the matrix, for example raw deviations ("deviations") or deviation z-scores ("z") for a chromVAR deviations matrix.
`verbose`	A boolean value that determines whether standard output is printed.
`logFile`	The path to a file to be used for logging ArchR output.