pathway_enrich_internal: Pathway enrichment for cellWeighted_Foldchange's and bulk...
In DustinSokolowski/scMappR: Single Cell Mapper

Description Usage Arguments Details Value Examples

View source: R/pathway_enrich_internal.R

This function completes pathway enrichment of cellWeighted_Foldchanges and bulk gene list.

pathway_enrich_internal(
  DEGs,
  theSpecies,
  scMappR_vals,
  background_genes,
  output_directory,
  plot_names,
  number_genes = -9,
  newGprofiler = FALSE,
  toSave = FALSE,
  path = NULL
)

`DEGs`	Differentially expressed genes (gene_name, padj, log2fc).
`theSpecies`	Human, mouse, or a charcter that is compatible with gProfileR.
`scMappR_vals`	cell weighted Fold-changes of differentially expressed genes.
`background_genes`	A list of background genes to test against.
`output_directory`	Path to the directory where files will be saved.
`plot_names`	Names of output.
`number_genes`	Number of genes to if there are many, many DEGs.
`newGprofiler`	Whether to use gProfileR or gprofiler2 (T/F).
`toSave`	Allow scMappR to write files in the current directory (T/F).
`path`	If toSave == TRUE, path to the directory where files will be saved.

Internal: Pathway analysis of differentially expressed genes (DEGs) and cell weighted Fold-changes (cellWeighted_Foldchanges) for each cell-type. Returns .RData objects of differential analysis as well as plots of the top bulk pathways. It is a wrapper for making barplots, bulk pathway analysis, and gProfiler_cellWeighted_Foldchange.

List with the following elements:

`BPs`	Enriched biological pathways for each cell-type.
`TFs`	Enriched transcription factors for each cell-type.

data(PBMC_example)
bulk_DE_cors <- PBMC_example$bulk_DE_cors
bulk_normalized <- PBMC_example$bulk_normalized
odds_ratio_in <- PBMC_example$odds_ratio_in
case_grep <- "_female"
control_grep <- "_male"
max_proportion_change <- 10
print_plots <- FALSE
theSpecies <- "human"
toOut <- scMappR_and_pathway_analysis(bulk_normalized, odds_ratio_in, 
                                      bulk_DE_cors, case_grep = case_grep,
                                      control_grep = control_grep, rda_path = "", 
                                      max_proportion_change = 10, print_plots = TRUE, 
                                       plot_names = "tst1", theSpecies = "human", 
                                       output_directory = "tester",
                                       sig_matrix_size = 3000, up_and_downregulated = FALSE, 
                                       internet = FALSE)