View source: R/pathway_enrich_internal.R
pathway_enrich_internal | R Documentation |
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 character that is compatible with g:ProfileR. |
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 g:ProfileR 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)
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