generes_to_heatmap: Generate signature matrix

In scMappR: Single Cell Mapper

Generate signature matrix

Description

Convert a list of cell-type markers from FindMarkers in Seurat to a signature matrix defined by odds ratio and rank.

Usage

generes_to_heatmap(
  generes = generes,
  species = "human",
  naming_preference = -9,
  rda_path = "",
  make_names = TRUE,
  internal = FALSE
)

Arguments

generes	A list of cell-type markers with fold-changes and p-values (FindMarkers output in Seurat).
species	The species of gene symbols, if not internal, "human" or "mouse".
naming_preference	Likely cell-types given tissues (to be passed into human_mouse_ct_marker_enrich).
rda_path	Path to output direcotry, if toSave is true.
make_names	Identify names of cell-type markers using the Fisher's exact test method (T/F).
internal	If this function is pre-processing from Panglao (T/F).

Details

Take a list of compiled differentially expressed genes from different cell-types, identify what the cell-types are using the Fisher's exact test, and then convert into a signature matrix for both the adjusted p-value and odds ratio.

Value

List with the following elements:

pVal	A dataframe containing the signature matrix of ranks (-log10(Padj) * sign(fold-change)).
OR	A dataframe containing the signature matrix of odds ratios.
cellname	A vector of the cell-labels returned from the GSVA method.
topGenes	the top 30 mos expressed genes in each cell-type.

Examples

data(POA_example)
 POA_generes <- POA_example$POA_generes
signature <- generes_to_heatmap(POA_generes,species = -9, make_names = FALSE)

scMappR documentation built on July 9, 2023, 6:26 p.m.