Get GSEA Squared terms/keywords

Usage

get_GSEAsq_terms(
  df_GSEA,
  savename = NULL,
  filt_freq = c(5, 500),
  signlogp_base = 10,
  rep0 = .Machine$double.xmin,
  verbose = TRUE,
  plot = TRUE,
  plot_pval = 1e-05,
  plot_fmt = "png",
  seed = 13
)

Arguments

df_GSEA: df/string; (path to) GSEA results with pathway and NES columns
savename: string; path to save output under, no extension
filt_freq: num vector; frequency filter for terms, filt_freq[1] is minimum frequency, filt_freq[2] is maximum frequency
signlogp_base: integer; log base when calculating signed log_base p metric
rep0: numeric; value to replace pval == 0 results with, use rep0 = 2.2e-16 (rounded .Machine$double.eps) to be same as original function
verbose: logical; TRUE to output terms as KS p-value is being calculated
plot: logical; TRUE to output barplot of significant terms
plot_pval: numeric; include terms with pval <= plot_pval in barplot
plot_fmt: string; file extension to save plot as
seed: numeric; randomization seed

Value

df w/ terms, frequency, (KS) pval, signed enrichment score, and signlogp

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
# Load data
deseq_stats <- setNames(
  airway_deseq_res[,"sign_log_p"],
  airway_deseq_res[,"hgnc_symbol"]
)
pthwys <- GSEA_pathways
# Run (f)gsea
gsea_results <- fgsea::fgsea(
  pathways = pthwys,
  stats = deseq_stats,
  eps = 0.0,
  minSize = 15,
  maxSize  = 500) %>%
  arrange(NES)
#> Warning: There are ties in the preranked stats (6.92% of the list).
#> The order of those tied genes will be arbitrary, which may produce unexpected results.
# Get terms
head(Rubrary::get_GSEAsq_terms(gsea_results, verbose = FALSE))

#>            Term Freq         pval         ES signedlogp
#> 1     METABOLIC  256 1.998401e-15 -0.2663684 -14.699317
#> 2           DNA  130 1.895151e-12  0.3408557  11.722356
#> 3 MORPHOGENESIS  110 4.767242e-11  0.3370141  10.321733
#> 4          GENE   14 1.939423e-10  0.2515788   9.712327
#> 5         LIPID   55 8.623270e-10 -0.3655041  -9.064328
#> 6   DEVELOPMENT  219 8.624648e-10  0.2228497   9.064259