## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----load, message=FALSE------------------------------------------------------ library(dorothea) library(decoupleR) library(ggplot2) library(dplyr) ## ----model-------------------------------------------------------------------- net <- decoupleR::get_dorothea(levels = c('A', 'B', 'C', 'D')) head(net) ## ----n_genes------------------------------------------------------------------ n_genes <- net %>% group_by(source) %>% summarize(n = n()) ggplot(data=n_genes, aes(x=n)) + geom_density() + theme(text = element_text(size=12)) + xlab('Number of target genes') + ylab('densities') + theme_bw() + theme(legend.position = "none") ## ----n_edges------------------------------------------------------------------ n_edges <- net %>% group_by(confidence) %>% summarize(n = n()) ggplot(data=n_edges, aes(x=confidence, y=log10(n), color=confidence, fill=confidence)) + geom_bar(stat="identity") + theme(text = element_text(size=12)) + xlab('Confidence') + ylab('log10(Number of edges)') + theme_bw() + theme(legend.position = "none") ## ----prop--------------------------------------------------------------------- prop <- net %>% mutate(mor = case_when(mor < 0 ~ -1, mor > 0 ~ 1)) %>% group_by(source, mor) %>% summarize(n = n()) %>% mutate(freq = n / sum(n)) %>% filter(mor == 1) ggplot(data=prop, aes(x=freq)) + geom_density() + theme(text = element_text(size=12)) + xlab('% of positive edges') + ylab('densities') + theme_bw() + theme(legend.position = "none") ## ----collectri---------------------------------------------------------------- net <- decoupleR::get_collectri(split_complexes = FALSE) head(net) ## ----n_genes_collectri-------------------------------------------------------- n_genes <- net %>% group_by(source) %>% summarize(n = n()) ggplot(data=n_genes, aes(x=n)) + geom_density() + theme(text = element_text(size=12)) + xlab('Number of target genes') + ylab('densities') + theme_bw() + theme(legend.position = "none") ## ----prop_collectri----------------------------------------------------------- prop <- net %>% mutate(mor = case_when(mor < 0 ~ -1, mor > 0 ~ 1)) %>% group_by(source, mor) %>% summarize(n = n()) %>% mutate(freq = n / sum(n)) %>% filter(mor == 1) ggplot(data=prop, aes(x=freq)) + geom_density() + theme(text = element_text(size=12)) + xlab('% of positive edges') + ylab('densities') + theme_bw() + theme(legend.position = "none")