#' @title Wrapper function for circRNAs prediction using STARChip
#' @description This function calls sequentially the docker containers for FASTQC, STAR, and STARChip to predict the list of circRNAs starting from the raw RNA-Seq reads
#'
#' @param group, a character string. Two options: sudo or docker, depending to which group the user belongs
#' @param scratch.folder, a character string indicating the scratch folder where docker container will be mounted
#' @param genome.folder, a character string indicating the folder where the indexed reference genome for STAR is located.
#' @param samples.folder, the folder where are located all the subfolders of the samples processed with starChimeric
#' @param threads, a number indicating the number of cores to be used from the application
#' @param chimSegmentMin, is a positive integer indicating the minimal length of the overlap of a read to the chimeric element
#' @param chimJunctionOverhangMin, is a positive integer indicating the minimum overhang for a chimeric junction
#' @param reads.cutoff, Integer. Minimum number of reads crossing the circRNA backsplice required.
#' @param min.subject.limit, Integer. Minimum number of individuals with readsCutoff reads required to carry forward a circRNA for analysis
#' @param do.splice, true false. The splices within the circRNA be detected and reported. Linear splices are searched within each circRNA in each individual. Any linear splice with >= 60\% of the read count of the cRNA is considered a splice within the circRNA. Two files are then created, .consensus with most common splice pattern, and .allvariants with all reported splice patterns.
#' @param cpm.cutoff, Float. Reads counts are loaded into R and log2(CountsPerMillion) is calculated using the limma package. With cpmCutoff > 0, circRNAs with log2(CPM) below this value will be filtered from this analysis
#' @param subjectCPM.cutoff, Integer. See above. This value is the lower limit for number of individuals required to have the circRNAs expressed at a value higher than cpmCutoff.
#' @param annotation, true/false. circRNAs are provided with gene annotations
#' @author Nicola Licheri, nicola [dot] licheri [at] unito [dot] it, University of Turin, Italy
#'
#' @return 1. Count matrices : raw cRNA backsplice counts: circRNA.cutoff[readthreshold]reads.[subjectthreshold]ind.countmatrix log2CPM of above: norm_log2_counts_circRNA.[readthreshold]reads.[subjectthreshold]ind.0cpm_0samples.txt Maximum Linear Splices at Circular Loci: rawdata/linear.[readthreshold]reads.[subjectthreshold]ind.sjmax 2. Info about each circRNA: Consensus Information about Internal Splicing: Circs[reads].[subjects].spliced.consensus Complete Gene Annotation: circRNA.[readthreshold]reads.[subjectthreshold]ind.annotated Consise Gene Annotation + Splice Type: circRNA.[readthreshold]reads.[subjectthreshold]ind.genes 3. Images: PCA plots: circRNA.[readthreshold]reads.[subjectthreshold]ind.0cpm_0samples_variance_PCA.pdf Heatmap: circRNA.[readthreshold]reads.[subjectthreshold]ind.heatmap.pdf
#' @examples
#' \dontrun{
#'
#' #retrieve the example data
#' system("wget https://github.com/carlo-deintinis/circhunter/archive/master.zip") #retrieve the data of the indexed genome (chromosome 21 of hg38 human genome assembly)
#' system("unzip master.zip")
#' system("unzip ./circhunter-master/CircHunter/data/hg38.chr21.fa.zip")
#' system("wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR582/001/SRR5824251/SRR5824251_1.fastq.gz") #retrieve the RNA-Seq data
#' system("wget ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR582/001/SRR5824251/SRR5824251_2.fastq.gz") #retrieve the RNA-Seq data
#'
#' #running the wrapperSTARChip function
#' wrapperSTARChip(group = "docker", scratch.folder="/data/scratch", genome.folder="./circhunter-master/CircHunter/data/", samples.folder=getwd(), threads = 8, chimSegmentMin = 20, chimJunctionOverhangMin = 15, reads.cutoff = 5, min.subject.limit = 1, do.splice = FALSE, cpm.cutoff = 0, subjectCPM.cutoff = 0, annotation = FALSE)
#'
#' }
#' @export
wrapperSTARChip <- function(group=c("sudo", "docker"),
#I/O parameters + #threads
scratch.folder, genome.folder, samples.folder, threads,
# STARChimeric parameters
chimSegmentMin, chimJunctionOverhangMin,
# STARChipCircle parameters
reads.cutoff, min.subject.limit, do.splice, cpm.cutoff, subjectCPM.cutoff, annotation) {
home <- getwd()
scratch.folder <- normalizePath(scratch.folder)
genome.folder <- normalizePath(genome.folder)
samples.folder <- normalizePath(samples.folder)
starChipIndex(group, genome.folder)
for (sample in list.dirs(path = samples.folder, full.names = TRUE)) {
if (sample != samples.folder) {
## Quality control using FASTQC
fastqc(group = group, data.folder = sample)
# moving FASTQC output in a subfolder
fastqc_files <- list.files(sample, full.names = TRUE)
fastqc_files <- fastqc_files[grep("_tmp_fastqc", fastqc_files)]
fastqc_output.folder <- file.path(sample, "fastqc_output")
if (!dir.exists(fastqc_output.folder)) {
dir.create(fastqc_output.folder)
}
system(paste("mv", paste(fastqc_files, collapse = " "), fastqc_output.folder))
## Chimeric transcripts detection
starChimeric(group = group, fastq.folder = sample, scratch.folder = scratch.folder,
genome.folder = genome.folder, threads = threads, chimSegmentMin = chimSegmentMin,
chimJunctionOverhangMin = chimJunctionOverhangMin)
}
}
## circRNA prediction
starchipCircle(group=group, scratch.folder=scratch.folder, genome.folder=genome.folder,
samples.folder=samples.folder, reads.cutoff=reads.cutoff, min.subject.limit=min.subject.limit,
threads=threads, do.splice=do.splice, cpm.cutoff=cpm.cutoff,
subjectCPM.cutoff=subjectCPM.cutoff, annotation=annotation)
setwd(home)
}
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