## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----message= FALSE, warning=FALSE-------------------------------------------- library(ceRNAnetsim) ## ----eval=FALSE--------------------------------------------------------------- # if (!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") # BiocManager::install("ceRNAnetsim") ## ----warning= FALSE, message=FALSE-------------------------------------------- data("mirtarbasegene") head(mirtarbasegene) ## ----------------------------------------------------------------------------- data("TCGA_E9_A1N5_normal") head(TCGA_E9_A1N5_normal) ## ----------------------------------------------------------------------------- data("TCGA_E9_A1N5_tumor") head(TCGA_E9_A1N5_tumor) ## ----------------------------------------------------------------------------- data("TCGA_E9_A1N5_mirnatumor") head(TCGA_E9_A1N5_mirnatumor) ## ----------------------------------------------------------------------------- data("TCGA_E9_A1N5_mirnanormal") head(TCGA_E9_A1N5_mirnanormal) ## ----------------------------------------------------------------------------- TCGA_E9_A1N5_mirnagene <- TCGA_E9_A1N5_mirnanormal %>% inner_join(mirtarbasegene, by= "miRNA") %>% inner_join(TCGA_E9_A1N5_normal, by = c("Target"= "external_gene_name")) %>% select(Target, miRNA, total_read, gene_expression) %>% distinct() ## ----echo=FALSE--------------------------------------------------------------- TCGA_E9_A1N5_mirnagene%>% group_by(Target, miRNA)%>% count()%>% filter(n==2) TCGA_E9_A1N5_mirnagene %>% group_by(Target) %>% mutate(gene_expression= max(gene_expression)) %>% distinct() %>% ungroup() -> TCGA_E9_A1N5_mirnagene ## ----------------------------------------------------------------------------- head(TCGA_E9_A1N5_mirnagene) ## ----------------------------------------------------------------------------- TCGA_E9_A1N5_mirnagene <- TCGA_E9_A1N5_mirnagene%>% filter(gene_expression > 10) ## ----warning=FALSE, fig.height=5, fig.width=6, fig.align='center', warning=FALSE---- simulation_res_HIST <- TCGA_E9_A1N5_mirnagene %>% priming_graph(competing_count = gene_expression, miRNA_count = total_read) %>% update_how(node_name = "HIST1H3H", how =30) %>% simulate(5) simulation_res_HIST%>% find_iteration(plot=TRUE) ## ----------------------------------------------------------------------------- simulation_res_HIST%>% as_tibble()%>% mutate(FC= count_current/initial_count)%>% arrange(desc(FC)) ## ----warning=FALSE, fig.height=5, fig.width=6, fig.align='center', warning=FALSE---- simulation_res_ACTB <- TCGA_E9_A1N5_mirnagene %>% priming_graph(competing_count = gene_expression, miRNA_count = total_read) %>% update_how(node_name = "ACTB", how =1.87) %>% simulate(5) simulation_res_ACTB%>% find_iteration(plot=TRUE) ## ----------------------------------------------------------------------------- simulation_res_ACTB%>% as_tibble()%>% mutate(FC= count_current/initial_count)%>% arrange(desc(FC)) ## ----message=FALSE, warning=FALSE--------------------------------------------- data("huge_example") head(huge_example) ## ----------------------------------------------------------------------------- filtered_example <- huge_example %>% add_count(competing) %>% filter(n > 5) %>% select(-n) head(filtered_example) ## ----fig.height=5, fig.width=6, fig.align='center', warning=FALSE------------- simulation_GAPDH <- filtered_example %>% priming_graph(competing_count = competing_counts, miRNA_count = mirnaexpression_normal, aff_factor = Energy) %>% update_how("GAPDH", 5) simulation_GAPDH%>% vis_graph(title = "Distribution of GAPDH gene node") ## ----fig.height=5, fig.width=6, fig.align='center', warning=FALSE, fig.show='hide'---- simulation_GAPDH%>% simulate_vis(title = "GAPDH over expression in the real dataset", 3) ## ----warning=FALSE------------------------------------------------------------ entire_perturbation <- filtered_example%>% priming_graph(competing_count = competing_counts, miRNA_count = mirnaexpression_normal)%>% find_node_perturbation(how=5, cycle=3, fast = 15)%>% select(name, perturbation_efficiency, perturbed_count) ## ----warning=FALSE------------------------------------------------------------ entire_perturbation%>% filter(!is.na(perturbation_efficiency), !is.na(perturbed_count))%>% select(name, perturbation_efficiency, perturbed_count) ## ----sessioninfo-------------------------------------------------------------- sessionInfo()