compute_pathway_activity: Compute pathway activity from gene expression using PROGENy

In olapuentesantana/easier: Estimate Systems Immune Response from RNA-seq data

Compute pathway activity from gene expression using PROGENy

Description

Infers pathway activity from counts bulk gene expression using PROGENy method from Holland et al., BBAGRM, 2019 and Schubert et al., Nat Commun, 2018.

Usage

compute_pathway_activity(
  RNA_counts = NULL,
  remove_sig_genes_immune_response = TRUE,
  verbose = TRUE
)

Arguments

RNA_counts	data.frame containing raw counts values with HGNC gene symbols as row names and samples identifiers as column names.
remove_sig_genes_immune_response	logical value indicating whether to remove signature genes involved in the derivation of hallmarks of immune response. This list is available from easierData package through easierData::get_cor_scores_genes().
verbose	logical value indicating whether to display messages about the number of pathway signature genes found in the gene expression data provided.

Value

A matrix of activity scores with samples in rows and pathways in columns.

References

Schubert M, Klinger B, Klunemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Bluthgen N, Saez-Rodriguez J. “Perturbation-response genes reveal signaling footprints in cancer gene expression.” Nature Communications: 10.1038/s41467-017-02391-6

Holland CH, Szalai B, Saez-Rodriguez J. "Transfer of regulatory knowledge from human to mouse for functional genomics analysis." Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 2019. DOI: 10.1016/j.bbagrm.2019.194431.

Examples

# using a SummarizedExperiment object
library(SummarizedExperiment)
# Using example exemplary dataset (Mariathasan et al., Nature, 2018)
# from easierData. Original processed data is available from
# IMvigor210CoreBiologies package.
library("easierData")

dataset_mariathasan <- easierData::get_Mariathasan2018_PDL1_treatment()
RNA_counts <- assays(dataset_mariathasan)[["counts"]]

# Select a subset of patients to reduce vignette building time.
pat_subset <- c(
  "SAM76a431ba6ce1", "SAMd3bd67996035", "SAMd3601288319e",
  "SAMba1a34b5a060", "SAM18a4dabbc557"
)
RNA_counts <- RNA_counts[, colnames(RNA_counts) %in% pat_subset]

# Computation of pathway activity
# (Holland et al., BBAGRM, 2019; Schubert et al., Nat Commun, 2018)
pathway_activity <- compute_pathway_activity(
  RNA_counts = RNA_counts,
  remove_sig_genes_immune_response = TRUE
)

olapuentesantana/easier documentation built on Feb. 25, 2024, 3:39 p.m.