Compute Single-sample Pathway-level Perturbation Score

Source: R/genePertScore.R

Sum gene-wise raw perturbation scores within each sample to derive single-sample perturbation scores for each pathway

pathway_pert(genePertScore)

Arguments

genePertScore

List of gene-wise raw perturbation score matrices generated using function raw_gene_pert()

Value

A data.frame with 3 columns: score (single-sample pathway-level perturbation score), sample, and gs_name (gene-set name)

References

Tarca AL, Draghici S, Khatri P, Hassan SS, Mittal P, Kim JS, Kim CJ, Kusanovic JP, Romero R. A novel signaling pathway impact analysis. Bioinformatics. 2009 Jan 1;25(1):75-82.

Examples

#compute weighted single sample logFCs
data(metadata_example)
data(logCPM_example)
metadata_example <- dplyr::mutate(metadata_example, treatment = factor(
   treatment, levels = c("Vehicle", "E2+R5020", "R5020")))
ls <- weight_ss_fc(logCPM_example, metadata = metadata_example,
groupBy = "patient", treatColumn = "treatment", sampleColumn = "sample")
# extract all the KEGG pathways
gsTopology <- retrieve_topology(database = "kegg", species = "hsapiens")
# compute raw gene-wise perturbation scores
genePertScore <- raw_gene_pert(ls$logFC, gsTopology)
# sum gene-wise perturbation scores to derive the pathway-level single-sample perturbation scores
pathwayPertScore <- pathway_pert( genePertScore)