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peak-summary-tools.R
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peak-summary-tools.R
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#!/usr/bin/env Rscript
# Run the ChIPSeeker pipeline on .BED files
# ~~~~~ PACKAGES ~~~~~ #
library("optparse")
library("tools")
library("grid")
library("gridExtra")
timestamp <- format(Sys.time(), "%Y-%m-%d-%H-%M-%S")
logfile <- file.path(".", sprintf("report_log.%s.txt", timestamp))
# default value, overwrite in report
is_report <- FALSE
# ~~~~~ FUNCTIONS ~~~~~ #
tsprintf <- function(fmt, ...){
# print a formatted message with timestamp
# base message
m <- sprintf(fmt, ...)
# message with timestamp
tm <- sprintf('[%s] %s', format(Sys.time(), "%H:%M:%S"), m)
# emit message
message(tm)
# add to log file
if(isTRUE(is_report)) cat(sprintf("%s\n", tm), file = logfile, append = TRUE)
}
msprintf <- function(fmt, ...) {
message(sprintf(fmt, ...))
}
mycat <- function(text){
# print formatted text in Rmd
cat(gsub(pattern = "\n", replacement = " \n", x = text))
}
make_filename <- function (input_file, new_ext, out_dir = FALSE) {
# Convert '/path/to/file.bed' to '/path/to/file_annotations.tsv'
old_ext <- file_ext(input_file)
filename_base <- gsub(pattern = sprintf('.%s$', old_ext), replacement = '', x = basename(input_file))
filename_new <- sprintf('%s.%s', filename_base, new_ext)
new_path <- file.path(dirname(input_file), filename_new)
if(out_dir != FALSE){
new_path <- file.path(out_dir, new_path)
dir.create(path = dirname(new_path), recursive = TRUE, showWarnings = FALSE)
}
return(new_path)
}
check_numlines <- function(input_file, min_value = 0) {
# make sure a file has >0 lines
has_enough_lines <- FALSE
if (length(readLines(input_file)) > min_value) has_enough_lines <- TRUE
return(has_enough_lines)
}
validate_file <- function(input_file) {
# make sure that all files are .bed, and that they have >0 lines
# validation passes if all files are .bed
all_exist <- all(file.exists(input_file))
if ( ! isTRUE(all_exist)) {
tsprintf("WARNING: Input file do not exist:\n%s\nFile will not be processed\n\n", input_file)
return(FALSE)
}
all_bed <- all(grepl(pattern = '*.bed$', x = basename(input_file)))
if ( ! isTRUE(all_bed)) {
tsprintf("WARNING: Input file is not .bed:\n%s\nFile will not be processed\n\n", input_file)
return(FALSE)
}
all_min_linenum <- all(sapply(input_file, check_numlines))
if ( ! isTRUE(all_min_linenum)) {
tsprintf("WARNING: Input file does not have enough lines:\n%s\nFile will not be processed\n\n", input_file)
return(FALSE)
}
return(TRUE)
}
find_all_beds <- function (input_dirs) {
# find all .bed files in the supplied dirs
return(dir(input_dirs, pattern = '.bed', full.names = TRUE, recursive = TRUE))
}
get_sampleID <- function(input_file, id_dirname = FALSE){
# get the sample ID for a file
# right now just use the basename but maybe some day do something fancier here
sampleID <- basename(input_file)
if(isTRUE(id_dirname)) sampleID <- basename(dirname(input_file))
return(sampleID)
}
get_sample_outdir <- function(parent_outdir, sampleID, create = TRUE){
# make a path for the sample's output directory
output_path <- file.path(parent_outdir, sampleID)
if(isTRUE(create)) dir.create(output_path, recursive = TRUE)
return(output_path)
}
chipseeker_pipeline <- function(bed_file, sampleID, tss_dist, txdb, out_dir = FALSE, annoDb = "org.Hs.eg.db"){
# the pipeline for ChIPSeeker peak annotations and plots
# list to hold output data
output_list <- list()
output_list[["plots"]] <- list()
# read in the peaks
tsprintf("Reading peaks file...\n\n")
peak <- readPeakFile(bed_file)
# make coverage plot
peaks_coverage_plot_file <- make_filename(input_file = bed_file, new_ext = 'coverage.pdf', out_dir = out_dir)
tsprintf("Making Chrom Coverages plot:\n%s\n\n", peaks_coverage_plot_file)
sample_title <- paste0(sampleID, " ChIP Peaks over Chromosomes")
pdf(file = peaks_coverage_plot_file)
output_list[["plots"]][["covplot"]] <- covplot(peak, weightCol = "V5", title = sample_title)
print(output_list[["plots"]][["covplot"]]) # title = "ChIP Peaks over Chromosomes"
dev.off()
# make annotations
tsprintf("Getting peak annotations...\n\n")
peakAnno <- annotatePeak(peak, tssRegion = c(-tss_dist, tss_dist),
TxDb = txdb,
annoDb = annoDb)
peak_anno_table_file <- make_filename(input_file = bed_file, new_ext = 'peak_anno.tsv', out_dir = out_dir)
tsprintf("Saving table:\n%s\n\n", peak_anno_table_file)
output_list[["peakAnno"]] <- peakAnno
write.table(output_list[["peakAnno"]], quote=FALSE, sep="\t", row.names =FALSE, file=peak_anno_table_file)
peak_anno_stats_file <- make_filename(input_file = bed_file, new_ext = 'peak_anno_stats.tsv', out_dir = out_dir)
tsprintf("Saving table:\n%s\n\n", peak_anno_stats_file)
output_list[["annoStat"]] <- peakAnno@annoStat
write.table(output_list[["annoStat"]], quote=FALSE, sep="\t", row.names =FALSE, file=peak_anno_stats_file)
tss_dist_file <- make_filename(input_file = bed_file, new_ext = 'tss_distance.txt', out_dir = out_dir)
tsprintf("Saving table:\n%s\n\n", tss_dist_file)
output_list[["tss_dist"]] <- tss_dist
cat(as.character(output_list[["tss_dist"]]), file = tss_dist_file)
# make annot pie chart
anno_piechart_plot_file <- make_filename(input_file = bed_file, new_ext = 'anno-piechart.pdf', out_dir = out_dir)
tsprintf("Making Peak Anno pie chart:\n%s\n\n", anno_piechart_plot_file)
sample_title <- paste0("\n\n", sampleID, " Peak Types")
output_list[["plots"]][["plotAnnoPie_sample_title"]] <- sample_title
pdf(file = anno_piechart_plot_file, height = 8, width = 8)
output_list[["plots"]][["plotAnnoPie"]] <- plotAnnoPie(peakAnno, main = sample_title)
print(output_list[["plots"]][["plotAnnoPie"]])
dev.off()
# make UpSet plot
tsprintf("Making Upset plot...\n\n")
# upset_plot_file <- file.path(output_directory, sprintf("%s_upsetplot.pdf", sampleID))
upset_plot_file <- make_filename(input_file = bed_file, new_ext = 'upsetplot.pdf', out_dir = out_dir)
sample_title <- paste0(sampleID, " Peak Overlaps")
output_list[["plots"]][["upsetplot_sample_title"]] <- sample_title
pdf(file = upset_plot_file, width = 9, height = 4.5, onefile = F)
output_list[["plots"]][["upsetplot"]] <- upsetplot(peakAnno, vennpie=TRUE)
print(output_list[["plots"]][["upsetplot"]])
text(x = 0, y = 1, sample_title) # add a title
dev.off()
return(output_list)
}
summarize_beds <- function(bed_files, tss_dist, id_dirname = FALSE, out_dir = FALSE, txdb_file = "TxDb.Hsapiens.UCSC.hg19.knownGene.Rdata") {
# run the ChIPSeeker pipeline on all the .bed files
# ~~~~~ VALIDATION ~~~~~ #
# check to make sure at least one files has >0 lines before we try to load data, because it takes a while to load
any_min_linenum <- any(sapply(names(bed_files), check_numlines))
if ( ! isTRUE(any_min_linenum)) {
tsprintf("ERROR: No input files have enough lines to be processed\nExiting...\n\n")
quit()
}
# ~~~~~ LOAD DATA ~~~~~ #
message("\nLoading packages and data...\n")
# source("http://bioconductor.org/biocLite.R")
# biocLite("ChIPseeker")
suppressPackageStartupMessages(library("ChIPseeker"))
suppressPackageStartupMessages(library("clusterProfiler"))
suppressPackageStartupMessages(library("TxDb.Hsapiens.UCSC.hg19.knownGene"))
# load data from saved Rdata file if it exists
if(file.exists(txdb_file)){
# txdb <- load(txdb_file)
# TODO: fix this, does not load correctly
txdb <- get("TxDb.Hsapiens.UCSC.hg19.knownGene")
} else {
txdb <- get("TxDb.Hsapiens.UCSC.hg19.knownGene")
}
# ~~~~~ RUN ~~~~~ #
# list to hold the output data
output_list <- list()
# iterate over bed files
tsprintf('\n------------------------------\n')
tsprintf('\n------------------------------\n')
for(i in seq_along(bed_files)){
bed_file <- names(bed_files[i])
process_file <- bed_files[i] # TRUE or FALSE
files_errors <- character()
files_warnings <- character()
tsprintf("Input File:\n%s\n\n\nFile will be processed:\n%s\n\n", bed_file, process_file)
if(isTRUE(as.logical(process_file))){
sampleID <- get_sampleID(input_file = bed_file, id_dirname = id_dirname)
tsprintf("Sample ID:\n%s\n\n\n", sampleID)
result <- tryCatch(
{
tsprintf("Running ChIPSeeker pipeline for sample %s, file:\n%s\n\n", sampleID, bed_file)
chipseeker_pipeline_output <- chipseeker_pipeline(bed_file = bed_file,
sampleID = sampleID,
tss_dist = tss_dist,
txdb = txdb,
out_dir = out_dir)
output_list[[sampleID]] <- list()
output_list[[sampleID]][["pipeline_output"]] <- chipseeker_pipeline_output
output_list[[sampleID]][["bed_file"]] <- bed_file
output_list[[sampleID]][["process_file"]] <- process_file
},
error = function(cond) {
tsprintf("An error occured while running ChIPSeeker pipeline for sample %s, file:\n%s\n\n", sampleID, bed_file)
message("Original error message:")
message(cond)
return("error")
},
warning = function(cond) {
tsprintf("An warning occured while running ChIPSeeker pipeline for sample %s, file:\n%s\n\n", sampleID, bed_file)
message("Original warning message:")
message(cond)
return("warning")
},
finally={
tsprintf("Finished running ChIPSeeker pipeline for sample %s, file:\n%s\n\n", sampleID, bed_file)
}
)
if(result == "error") files_errors <- c(files_errors, bed_file)
if(result == "warning") files_warnings <- c(files_warnings, bed_file)
}
tsprintf('\n------------------------------\n')
}
tsprintf('The following files had errors:\n')
tsprintf('%s\n', files_errors)
tsprintf('The following files had warnings:\n')
tsprintf('%s\n', files_warnings)
cat(files_errors, file = "file_errors.txt", append = TRUE)
cat(files_warnings, file = "file_warnings.txt", append = TRUE)
return(output_list)
}
sysinfo <- function(){
# print custom information about the system
# check if 'mycat' is loaded in case I copy/pasted this from elsewhere
if( ! exists('mycat')) mycat <- function(text){cat(gsub(pattern = "\n", replacement = " \n", x = text))}
# system info for use on Linux with GNU tools installed
# mycat(sprintf("System:\n%s\n%s", system("hostname", intern = TRUE), system("uname -srv", intern = TRUE)))
# mycat(sprintf("System user:\n%s", system("whoami", intern = TRUE)))
# dir
# mycat(sprintf("System location:\n%s", system('pwd', intern = T, ignore.stderr = TRUE)))
mycat(sprintf("System location:\n%s", getwd()))
# repo info
mycat(sprintf("Git Remote:\n%s\n", system('git remote -v', intern=T)))
mycat(sprintf("Git branch and commit\n%s", system('printf "%s: %s" "$(git rev-parse --abbrev-ref HEAD)" "$(git rev-parse HEAD)"',
intern = TRUE, ignore.stderr = TRUE)))
# date time
mycat(sprintf("Time and Date of report creation:\n%s", system("date", intern = TRUE)))
# R system info, packages, etc
print(sessionInfo())
print(Sys.info())
}