wrapper function to perform enrichment analysis with enrichr and save results
Usage
enrichrRun(
sheet,
dir_input = ".",
filename,
dir_output = ".",
dbs,
fc_thresh = 1,
p_thresh = 0.001,
remove_rp_mt
)Arguments
- sheet
sheet name in excel file
- dir_input
path to the directory where the deg file is located (default: .)
- filename
name of deg file file (should be .xlsx) without extension
- dir_output
path to the directory where the results will be saved (default: .)
- dbs
name of the enrichr libraries
- fc_thresh
log fc threshold (default 1)
- p_thresh
p value threshold (default 0.001)
- remove_rp_mt
remove ribosomal and mitochondrial genes? (boolean value)
Value
save enrichrment analysis in dir_output in two excel sheets (one for positive and one for negative)
Examples
library(Seurat)
library(enrichR)
#> Welcome to enrichR
#> Checking connection ...
#> Enrichr ...
#> Connection is Live!
#> FlyEnrichr ...
#> Connection is Live!
#> WormEnrichr ...
#> Connection is Live!
#> YeastEnrichr ...
#> Connection is Live!
#> FishEnrichr ...
#> Connection is Live!
#> OxEnrichr ...
#> Connection is Live!
set.seed(123)
deg_data <- data.frame(
gene = rownames(pbmc_small),
avg_log2FC = rnorm(length(rownames(pbmc_small)), mean = 0, sd = 3),
p_val_adj = runif(length(rownames(pbmc_small)), min = 0, max = 0.01)
)
writexl::write_xlsx(deg_data, path = "test_de.xlsx")
enrichrRun(
sheet = "Sheet1",
dir_input = ".",
filename = "test_de",
dbs = c("KEGG_2019_Human"),
fc_thresh = 1,
p_thresh = 0.001,
remove_rp_mt = FALSE
)
#> Uploading data to Enrichr... Done.
#> Querying KEGG_2019_Human... Done.
#> Parsing results... Done.
#> Uploading data to Enrichr... Done.
#> Querying KEGG_2019_Human... Done.
#> Parsing results... Done.
unlink("test_de.xlsx")
unlink("enrichr_test_de_neg_Sheet1.xlsx")
unlink("enrichr_test_de_pos_Sheet1.xlsx")