Pathway and TF activity analysis

Code

# Enrique Blanco Carmona
# e.blancocarmona@kitz-heidelberg.de
# PhD Student – Clinical Bioinformatics
# Division of Pediatric Neurooncology (B062)
# DKFZ-KiTZ | Germany

# ------------------------------------------------------------------
# 10 - PROGENY ANALYSIS
# ------------------------------------------------------------------

# Retrieve the merged LGG: OD + AS dataset.
sample <- readRDS("/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/datasets/integrated_LGGs.rds")

# And the labels from OD and AS.
labels.astro <- readRDS("/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/datasets/labels_primary_AS.rds")
labels.oligo <- readRDS("/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/datasets/labels_primary_OD.rds")
labels.use <- c(labels.astro, labels.oligo)
sample$relabelling <- labels.use

# Subset for tumor cells.
sample <- sample[, sample$relabelling %in% c("Astro-like", "RA", "OPC-like", "Gradient", "Cycling")]

# Since our datasets are quite large, it is not possible to run them at once in R.
# Therefore, we generate chunks and then combine the scores back to a single matrix.
# Will contain the results of the chunks.
dorothea_vector <- list()
progeny_vector <- list()


# Retrieve prior-knowledge networks.
dorothea_network <- decoupleR::get_dorothea(organism = "human",
                                            levels = c("A", "B", "C"))

progeny_network <- decoupleR::get_progeny(organism = "human")

# This for loop is tailored to our dataset.
# Chunks of 10000 cells.
for (i in 0:11){
  values <- c((10000 * i) + 1, (10000 * i) + 10000)
  if (i == 11){
    values[2] <- 119424 # Max cells.
  }
  values <- seq(from = values[1], to = values[2], by = 1)
  
  # Subset sample.
  sample.use <- sample[, colnames(sample)[values]]
  
  # Run dorothea.
  activities <- decoupleR::run_wmean(mat = as.matrix(sample.use@assays[["SCT"]]@data),
                                     network = dorothea_network,
                                     .source = "source",
                                     .targe = "target",
                                     .mor = "mor",
                                     times = 100,
                                     minsize = 5)
  dorothea_vector[[paste0("Iteration_", i)]] <- activities

  # Run progeny.
  activities <- decoupleR::run_wmean(mat = as.matrix(sample.use@assays[["SCT"]]@data),
                                     network = progeny_network,
                                     .source = "source",
                                     .targe = "target",
                                     .mor = "weight",
                                     times = 100,
                                     minsize = 5)
  progeny_vector[[paste0("Iteration_", i)]] <- activities
}

# Save results.
dorothea_activities <- rbind(dorothea_vector$Iteration_0,
                             dorothea_vector$Iteration_1,
                             dorothea_vector$Iteration_2,
                             dorothea_vector$Iteration_3,
                             dorothea_vector$Iteration_4,
                             dorothea_vector$Iteration_5,
                             dorothea_vector$Iteration_6,
                             dorothea_vector$Iteration_7,
                             dorothea_vector$Iteration_8,
                             dorothea_vector$Iteration_9,
                             dorothea_vector$Iteration_10,
                             dorothea_vector$Iteration_11)
saveRDS(dorothea_activities, "/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/main/TF_Pathway_analysis/primary_dorothea.rds")


# Retrieve prior knowledge network.

message("Saving Progeny results.")
progeny_activities <- rbind(progeny_vector$Iteration_0,
                            progeny_vector$Iteration_1,
                            progeny_vector$Iteration_2,
                            progeny_vector$Iteration_3,
                            progeny_vector$Iteration_4,
                            progeny_vector$Iteration_5,
                            progeny_vector$Iteration_6,
                            progeny_vector$Iteration_7,
                            progeny_vector$Iteration_8,
                            progeny_vector$Iteration_9,
                            progeny_vector$Iteration_10,
                            progeny_vector$Iteration_11)
saveRDS(progeny_activities, "/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/main/TF_Pathway_analysis/primary_progeny.rds")