Nothing
## ----echo=FALSE---------------------------------------------------------------
knitr::opts_chunk$set(warning=FALSE,
message=FALSE,
width=500)
options(max.print=35)
library("ggplot2")
library("data.table")
## -----------------------------------------------------------------------------
scores <- read.table(
system.file('extdata', 'Adenocarcinoma_scores_subset.tsv', package = 'ActivePathways'),
header = TRUE, sep = '\t', row.names = 'Gene')
scores <- as.matrix(scores)
scores
## -----------------------------------------------------------------------------
scores[is.na(scores)] <- 1
## -----------------------------------------------------------------------------
library(ActivePathways)
gmt_file <- system.file('extdata', 'hsapiens_REAC_subset.gmt', package = 'ActivePathways')
ActivePathways(scores, gmt_file)
## -----------------------------------------------------------------------------
fname_data_matrix <- system.file('extdata',
'Differential_expression_rna_protein.tsv',
package = 'ActivePathways')
pvals_FCs <- read.table(fname_data_matrix, header = TRUE, sep = '\t')
example_genes <- c('ACTN4','PIK3R4','PPIL1','NELFE','LUZP1','ITGB2')
pvals_FCs[pvals_FCs$gene %in% example_genes,]
## -----------------------------------------------------------------------------
pval_matrix <- data.frame(
row.names = pvals_FCs$gene,
rna = pvals_FCs$rna_pval,
protein = pvals_FCs$protein_pval)
pval_matrix <- as.matrix(pval_matrix)
pval_matrix[is.na(pval_matrix)] <- 1
pval_matrix[example_genes,]
## -----------------------------------------------------------------------------
dir_matrix <- data.frame(
row.names = pvals_FCs$gene,
rna = pvals_FCs$rna_log2fc,
protein = pvals_FCs$protein_log2fc)
dir_matrix <- as.matrix(dir_matrix)
dir_matrix <- sign(dir_matrix)
dir_matrix[is.na(dir_matrix)] <- 0
dir_matrix[example_genes,]
## -----------------------------------------------------------------------------
constraints_vector <- c(1,1)
constraints_vector
# constraints_vector <- c(1,-1)
## -----------------------------------------------------------------------------
directional_merged_pvals <- merge_p_values(pval_matrix,
method = "DPM", dir_matrix, constraints_vector)
merged_pvals <- merge_p_values(pval_matrix, method = "Brown")
sort(merged_pvals)[1:5]
sort(directional_merged_pvals)[1:5]
## -----------------------------------------------------------------------------
pvals_FCs[pvals_FCs$gene == "PIK3R4",]
pval_matrix["PIK3R4",]
dir_matrix["PIK3R4",]
merged_pvals["PIK3R4"]
directional_merged_pvals["PIK3R4"]
## -----------------------------------------------------------------------------
lineplot_df <- data.frame(original = -log10(merged_pvals),
modified = -log10(directional_merged_pvals))
ggplot(lineplot_df) +
geom_point(size = 2.4, shape = 19,
aes(original, modified,
color = ifelse(original <= -log10(0.05),"gray",
ifelse(modified > -log10(0.05),"#1F449C","#F05039")))) +
labs(title = "",
x ="Merged -log10(P)",
y = "Directional Merged -log10(P)") +
geom_hline(yintercept = 1.301, linetype = "dashed",
col = 'black', size = 0.5) +
geom_vline(xintercept = 1.301, linetype = "dashed",
col = "black", size = 0.5) +
geom_abline(size = 0.5, slope = 1,intercept = 0) +
scale_color_identity()
## -----------------------------------------------------------------------------
constraints_vector <- c(-1,1)
constraints_vector <- c(1,-1)
## -----------------------------------------------------------------------------
constraints_vector <- c(0,0)
## -----------------------------------------------------------------------------
constraints_vector <- c(1,-1)
## -----------------------------------------------------------------------------
constraints_vector <- c(1,1,-1)
## -----------------------------------------------------------------------------
fname_GMT2 <- system.file("extdata", "hsapiens_REAC_subset2.gmt",
package = "ActivePathways")
## -----------------------------------------------------------------------------
enriched_pathways <- ActivePathways(
pval_matrix, gmt = fname_GMT2, cytoscape_file_tag = "Original_")
constraints_vector <- c(1,1)
constraints_vector
dir_matrix[example_genes,]
enriched_pathways_directional <- ActivePathways(
pval_matrix, gmt = fname_GMT2, cytoscape_file_tag = "Directional_", merge_method = "DPM",
scores_direction = dir_matrix, constraints_vector = constraints_vector)
## -----------------------------------------------------------------------------
pathways_lost_in_directional_integration =
setdiff(enriched_pathways$term_id, enriched_pathways_directional$term_id)
pathways_lost_in_directional_integration
enriched_pathways[enriched_pathways$term_id %in% pathways_lost_in_directional_integration,]
## -----------------------------------------------------------------------------
wnt_pathway_id <- "REAC:R-HSA-3858494"
enriched_pathway_genes <- unlist(
enriched_pathways[enriched_pathways$term_id == wnt_pathway_id,]$overlap)
enriched_pathway_genes
## -----------------------------------------------------------------------------
pathway_gene_pvals = pval_matrix[enriched_pathway_genes,]
pathway_gene_directions = dir_matrix[enriched_pathway_genes,]
directional_conflict_genes = names(which(
pathway_gene_directions[,1] != pathway_gene_directions[,2] &
pathway_gene_directions[,1] != 0 & pathway_gene_directions[,2] != 0))
pathway_gene_pvals[directional_conflict_genes,]
pathway_gene_directions[directional_conflict_genes,]
length(directional_conflict_genes)
## -----------------------------------------------------------------------------
nrow(ActivePathways(scores, gmt_file, significant = 0.05))
nrow(ActivePathways(scores, gmt_file, significant = 0.1))
## -----------------------------------------------------------------------------
gmt <- read.GMT(gmt_file)
names(gmt[[1]])
# Pretty-print the GMT
gmt[1:3]
# Look at the genes annotated to the first term
gmt[[1]]$genes
# Get the full name of Reactome pathway 2424491
gmt$`REAC:2424491`$name
## -----------------------------------------------------------------------------
gmt <- Filter(function(term) length(term$genes) >= 10, gmt)
gmt <- Filter(function(term) length(term$genes) <= 500, gmt)
## -----------------------------------------------------------------------------
ActivePathways(scores, gmt)
## -----------------------------------------------------------------------------
ActivePathways(scores, gmt_file, geneset_filter = c(10, 500))
## ----eval=FALSE---------------------------------------------------------------
# write.GMT(gmt, 'hsapiens_REAC_subset_filtered.gmt')
## -----------------------------------------------------------------------------
background <- makeBackground(gmt)
background <- background[background != 'TP53']
ActivePathways(scores, gmt_file, background = background)
## -----------------------------------------------------------------------------
sort(merge_p_values(scores, 'Fisher'))[1:5]
sort(merge_p_values(scores, 'Brown'))[1:5]
sort(merge_p_values(scores, 'Stouffer'))[1:5]
sort(merge_p_values(scores, 'Strube'))[1:5]
## -----------------------------------------------------------------------------
scores2 <- cbind(scores[, 'CDS'], merge_p_values(scores[, c('X3UTR', 'X5UTR', 'promCore')], 'Brown'))
colnames(scores2) <- c('CDS', 'non_coding')
scores[c(2179, 1760),]
scores2[c(2179, 1760),]
ActivePathways(scores, gmt_file)
ActivePathways(scores2, gmt_file)
## -----------------------------------------------------------------------------
nrow(ActivePathways(scores, gmt_file))
nrow(ActivePathways(scores, gmt_file, cutoff = 0.01))
## -----------------------------------------------------------------------------
nrow(ActivePathways(scores, gmt_file))
nrow(ActivePathways(scores, gmt_file, correction_method = 'none'))
## -----------------------------------------------------------------------------
res <- ActivePathways(scores, gmt_file)
res
## -----------------------------------------------------------------------------
res$overlap[1:3]
## -----------------------------------------------------------------------------
unlist(res[res$term_id == "REAC:422475","evidence"])
## ----eval = FALSE-------------------------------------------------------------
# result_file <- paste('ActivePathways_results.csv', sep = '/')
# export_as_CSV (res, result_file) # remove comment to run
# read.csv(result_file, stringsAsFactors = F)[1:3,]
## ----eval=FALSE---------------------------------------------------------------
# result_file <- paste('ActivePathways_results2.txt', sep = '/')
# data.table::fwrite(res, result_file, sep = '\t', sep2 = c('', ',', ''))
# cat(paste(readLines(result_file)[1:2], collapse = '\n'))
## ----eval=FALSE---------------------------------------------------------------
# res <- ActivePathways(scores, gmt_file, cytoscape_file_tag = "enrichmentMap__")
## -----------------------------------------------------------------------------
files <- c(system.file('extdata', 'enrichmentMap__pathways.txt', package='ActivePathways'),
system.file('extdata', 'enrichmentMap__subgroups.txt', package='ActivePathways'),
system.file('extdata', 'enrichmentMap__pathways.gmt', package='ActivePathways'),
system.file('extdata', 'enrichmentMap__legend.pdf', package='ActivePathways'))
## ----eval=FALSE---------------------------------------------------------------
# gmt_file <- system.file('extdata', 'hsapiens_REAC_subset.gmt', package = 'ActivePathways')
# scores_file <- system.file('extdata', 'Adenocarcinoma_scores_subset.tsv', package = 'ActivePathways')
#
# scores <- read.table(scores_file, header = TRUE, sep = '\t', row.names = 'Gene')
# scores <- as.matrix(scores)
# scores[is.na(scores)] <- 1
#
# res <- ActivePathways(scores, gmt_file, cytoscape_file_tag = "enrichmentMap__")
## -----------------------------------------------------------------------------
cat(paste(readLines(files[1])[1:5], collapse='\n'))
cat(paste(readLines(files[2])[1:5], collapse='\n'))
cat(paste(readLines(files[3])[18:19], collapse='\n'))
## -----------------------------------------------------------------------------
res <- ActivePathways(scores, gmt_file, cytoscape_file_tag = "enrichmentMap__", color_palette = "Pastel1")
## -----------------------------------------------------------------------------
res <- ActivePathways(scores, gmt_file, cytoscape_file_tag = "enrichmentMap__", custom_colors = c("violet","green","orange","red"))
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.