## ----eval = TRUE, echo = TRUE, message = FALSE-------------------------------- library(ORFik) ## ----eval = TRUE, echo = TRUE------------------------------------------------- # Read from (create.experiment() template) # 1. Pick directory (normally a folder with bam / bed / wig files) dir <- system.file("extdata", "", package = "ORFik") list.files(dir) ## ----eval = TRUE, echo = TRUE------------------------------------------------- # 2. Pick an experiment name exper <- "ORFik" # 3. Pick .gff/.gtf and fasta location txdb <- system.file("extdata", "annotations.gtf", package = "ORFik") fasta <- system.file("extdata", "genome.fasta", package = "ORFik") template <- create.experiment(dir = dir, # dir is the NGS files exper, # Experiment name txdb = txdb, # gtf / gff / gff.db annotation fa = fasta, # Fasta genome organism = "Homo sapiens", # Scientific naming saveDir = NULL, # If not NULL, saves experiment directly viewTemplate = FALSE) data.frame(template) ## ----eval = TRUE, echo = TRUE------------------------------------------------- template$X5[6] <- "heart_valve" # <- fix non unique row (tissue fraction is heart valve) # read experiment from template df <- read.experiment(template) ## ----eval = FALSE, echo = TRUE------------------------------------------------ # save.experiment(df, file = "path/to/save/experiment.csv") ## ----eval = TRUE, echo = TRUE------------------------------------------------- df ## ----eval = TRUE, echo = TRUE------------------------------------------------- filepath(df, type = "default") ## ----eval = TRUE, echo = TRUE, warning = FALSE-------------------------------- # First load experiment if not present # We use our already loaded experiment: (df) here # Load transcript annotation txdb <- loadTxdb(df) # transcript annotation # And now NGS data outputLibs(df, chrStyle = seqlevelsStyle(txdb)) # Use txdb as seqlevelsStyle reference ## ----eval = TRUE, echo = TRUE------------------------------------------------- bamVarName(df) #This will be the names: ## ----eval = TRUE, echo = TRUE------------------------------------------------- df@expInVarName <- TRUE bamVarName(df) #This will be the names: ## ----eval = TRUE, echo = TRUE------------------------------------------------- df@expInVarName <- FALSE remove.experiments(df) outputLibs(df, chrStyle = seqlevelsStyle(txdb)) ## ----eval = TRUE, echo = TRUE------------------------------------------------- txNames <- filterTranscripts(txdb, minFiveUTR = 30,minCDS = 30, minThreeUTR = 30) loadRegions(txdb, parts = c("leaders", "cds", "trailers"), names.keep = txNames) ## ----eval = TRUE, echo = TRUE, warning=FALSE---------------------------------- transcriptWindow(leaders, cds, trailers, df[3,]) ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # shiftFootprintsByExperiment(df[df$libtype == "RFP",]) ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # df.baz <- read.experiment("zf_bazzini14_RFP") # shiftPlots(df.baz, title = "Ribo-seq, zebrafish, Bazzini et al. 2014") ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # shifts.load(df) ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # filepath(df[df$libtype == "RFP",], type = "pshifted") ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # outputLibs(df[df$libtype == "RFP",], type = "pshifted") ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # QCreport(df) ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # QCstats(df) ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # RiboQC.plot(df) ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # outputLibs(df, type = "pshifted") # Output all libraries, fastest way # libs <- bamVarName(df) # <- here are names of the libs that were outputed # cds <- loadRegion(df, "cds") # # parallel loop # bplapply(libs, FUN = function(lib, cds) { # return(entropy(cds, get(lib))) # }, cds = cds) # ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # files <- filepath(df, type = "pshifted") # cds <- loadRegion(df, "cds") # # parallel loop # res <- bplapply(files, FUN = function(file, cds) { # return(entropy(cds, fimport(file))) # }, cds = cds) # ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # files <- filepath(df, type = "pshifted") # cds <- loadRegion(df, "cds") # # Single thread loop # lapply(files, FUN = function(file, cds) { # return(entropy(cds, fimport(file))) # }, cds = cds) # ## ----eval = FALSE, echo = TRUE, warning=FALSE--------------------------------- # library(data.table) # # outputLibs(df, type = "pshifted") # libs <- bamVarName(df) # <- here are names of the libs that were outputed # cds <- loadRegion(df, "cds") # # parallel loop # res <- bplapply(libs, FUN = function(lib, cds) { # return(entropy(cds, get(lib))) # }, cds = cds) # # Add some names and convert # names(res) <- libs # data.table::setDT(res) # Will give 1 column per library # res # Now by columns