# Calculate Area Under Curve (AUC) and Differences of AUC for Transcript Data This function computes the Area Under Curve (AUC) and the differences of AUC between two conditions for a list of transcript data. It supports parallel computation for efficiency. If only one condition is given, the differences are not computed. ```r allauc(bytranslistmean, expdf, nbwindows, nbcpu = 1, controlcondname = "ctrl", stresscondname = "HS", showtime = FALSE, verbose = TRUE) ``` ## Arguments - `bytranslistmean`: A list of data frames, each containing transcript level data with mean values for one or more conditions. - `expdf`: A data frame containing experiment data that should have columns named 'condition', 'replicate', 'strand', and 'path'. - `nbwindows`: An integer specifying the number of windows to consider for AUC calculations. - `nbcpu`: An integer specifying the number of CPU cores to use for parallel processing on bytranslistmean. Defaults to `1`. - `controlcondname`: A string specifying the name of the control condition Defaults to `"ctrl"`. - `stresscondname`: A string specifying the name of the stress condition. Defaults to `"HS"`. - `showtime`: A logical value indicating if the duration of the function processing should be indicated before ending. Defaults to `FALSE`. - `verbose`: A logical value indicating whether to print progress messages Defaults to `TRUE`. ## Returns A data frame containing the AUC and dAUC results for each transcript, along with associated statistical information. ## Details The function first checks if exactly two conditions are present in `expdf`. If so, it computes the differences in AUC between the two conditions using a Kolmogorov-Smirnov test. It then calculates the AUC for all conditions against a reference line (y=x). Results are merged by transcript and include adjusted p-values. ## Examples ```r exppath <- system.file("extdata", "exptab.csv", package="tepr") transpath <- system.file("extdata", "cugusi_6.tsv", package="tepr") expthres <- 0.1 ## Reading tables expdf <- read.csv(exppath) transdf <- read.delim(transpath, header = FALSE) ## Computing intermediate steps avfilt <- averageandfilterexprs(expdf, transdf, expthres, showtime = FALSE, verbose = FALSE) ecdf <- genesECDF(avfilt, expdf, verbose = FALSE) resecdf <- ecdf[[1]] nbwindows <- ecdf[[2]] meandiff <- meandifference(resecdf, expdf, nbwindows, verbose = FALSE) bytranslistmean <- split(meandiff, factor(meandiff$transcript)) ## Testing allauc res <- allauc(bytranslistmean, expdf, nbwindows, verbose = FALSE) ``` ## See Also [genesECDF]

allauc function