Diffusion maps

Code

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

# ------------------------------------------------------------------
# 12 - DIFFUSION MAPS
# ------------------------------------------------------------------

# Load dataset with OD + AS cells.
sample <- readRDS("/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/datasets/integrated_LGGs.rds")

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

# Load markers from Mario Suva's publication.
markers.suva <- readRDS("/omics/odcf/analysis/OE0145_projects/idh_gliomas/Figures_Science/revision/datasets/IDH_gliomas_TB_annotation_kit_with_Suva_programs_and_metaprogram_iterations.rds")
markers <- list()
markers$Stemness_Program <- markers.suva$Stemness_Program
markers$Oligo_Program <- markers.suva$Oligo_Program
markers$Astro_Program <- markers.suva$Astro_Program

# Pull the genes into a vector.
markers.use <- unlist(markers) %>% unname() %>% unique()

# Subset the genes present in the assay.
markers.use <- markers.use[markers.use %in% rownames(sample)]

# Reduce the count matrix to only these genes.
sample <- sample[markers.use, ]

# Transform from Seurat to SCE.
sample <- Seurat::as.SingleCellExperiment(sample,
                                          assay = "SCT")

diff.map <- destiny::DiffusionMap(sample, verbose = T)