HDStIM: HDStIM: High Dimensional Stimulation Immune Mapping

View source: R/HDStIM.R

HDStIMR Documentation

HDStIM: High Dimensional Stimulation Immune Mapping

Description

Function to select cells from the stimulated samples that have likely responded to the stimulant.

Usage

HDStIM(
  dat,
  state_markers,
  cellpop_col,
  stim_lab,
  unstim_lab,
  p_value = 0.05,
  seed_val = NULL,
  umap = FALSE,
  umap_cells = NULL,
  verbose = FALSE
)

Arguments

dat

A tibble with the single cell data. Cells on rows and variables/markers on columns.

state_markers

A character vector with the labels of state markers from the stimulation panel.

cellpop_col

Column in the tibble with the cell population IDs.

stim_lab

A character vector of stim label(s).

unstim_lab

A character of unstim label(s).

p_value

The P-value for Fisher's exact test. Default is 0.05.

seed_val

Seed value (integer) for kmeans clustering. Default is NULL for no seed value.

umap

Boolean (T/F) to carry out UMAP on the selected cells. Default is FALSE to skip UMAP calculation.

umap_cells

An integer; for calculating UMAPs take a minimum of umap_cells per cluster or the total number of cells if the cluster size is smaller than umap_cells. Default is NULL.

verbose

Logical. To make function more verbose. Default is FALSE.

Value

A list with tibbles for expression data for the selected cells, data to plot stacked bar plots, data to plot UMAP plots, and parameters passed to the function.

Examples

mapped_data <- HDStIM(chi11$expr_data, chi11$state_markers,
                  chi11$cluster_col, chi11$stim_label,
                  chi11$unstim_label, seed_val = 123, umap = FALSE, umap_cells = NULL,
                  verbose = FALSE)

niaid/HDStIM documentation built on Oct. 15, 2023, 4:43 p.m.