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generate_objects.R
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# Copyright (c) [2020] [Ricardo O. Ramirez Flores]
#'Generates visium objects + qc + funcomics + differential expression analysis
library(tidyverse)
library(Seurat)
library(clustree)
library(progeny)
library(dorothea)
library(cowplot)
source("visiumtools/reading2clustering.R")
source("visiumtools/funcomics.R")
source("visiumtools/differential_test.R")
source("visiumtools/misty_pipelines.R")
source("visiumtools/misty_utils.R")
sample_ids = set_names(c("V19S23-097_A1","V19S23-097_B1",
"V19S23-097_C1", "V19S23-097_D1"))
colon_slides = c("V19S23-097_A1","V19S23-097_B1")
marker_df_e = read_delim(file = "markers/Epithelial_Marker_genes_colon.csv",
delim = ",") %>%
arrange(cluster, p_val_adj) %>%
select(gene, avg_logFC, cluster) %>%
group_by(cluster) %>%
slice(1:200) %>%
ungroup() %>%
mutate(cluster = paste0("Epithelial_c",cluster))
marker_df_s = read_delim(file = "markers/Stromal_Marker_genes_colon.csv",
delim = ",") %>%
arrange(cluster, p_val_adj) %>%
select(gene, avg_logFC, cluster) %>%
group_by(cluster) %>%
slice(1:200) %>%
ungroup() %>%
mutate(cluster = paste0("Stromal_c",cluster))
marker_df = bind_rows(marker_df_e, marker_df_s)
for(slide in sample_ids){
print(slide)
slide_dir = sprintf("./results/single_slide/%s",slide)
#system(paste0("mkdir results/single_slide/",slide))
slide_out = sprintf("results/single_slide/%s/%s.rds",
slide,slide)
slide_dea = sprintf("results/single_slide/%s/%s_diff_features.rds",
slide,slide)
visium_slide = process_visium(dir_path = slide,
var_features = "seurat",
p_value_thrsh = NULL,
out_dir = slide_dir,
resolution = 1,
verbose = FALSE)
if(slide %in% colon_slides){
visium_slide = add_funcomics(visium_slide = visium_slide,
species = "mouse",
confidence_lbls = c("A","B","C"),
top = 1000,
marker_df = marker_df,
verbose = FALSE)
differential_features = find_allfeat(visium_slide = visium_slide,
assays_collection = c("SCT",
"dorothea",
"progeny",
"ctscores"))
}else{
visium_slide = add_funcomics(visium_slide = visium_slide,
species = "mouse",
confidence_lbls = c("A","B","C"),
top = 1000,
marker_df = NULL,
verbose = FALSE)
# Perform differential expression analysis of features in all assays
# Warning: By default I am running Wilcox tests, because they seem
# to work good enough for characterization purposes
differential_features = find_allfeat(visium_slide = visium_slide,
assays_collection = c("SCT",
"dorothea",
"progeny"))
}
saveRDS(visium_slide,
file = slide_out)
saveRDS(differential_features, file = slide_dea)
}