1d:T772,# Identify the Knee and Max ECDF Differences for Each Transcript This function identifies the knee point (i.e., point of maximum change) and the maximum difference in the empirical cumulative distribution function (ECDF) for each transcript, across different experimental conditions. ```r kneeid(transdflist, expdf, nbcpu = 1, showtime = FALSE, verbose = TRUE) ``` ## Arguments - `transdflist`: A list of data frames where each data frame contains transcript data with ECDF values for each condition. - `expdf`: A data frame containing experiment data that should have columns named 'condition', 'replicate', 'strand', and 'path'. - `nbcpu`: An integer specifying the number of CPU cores to use for parallel computation. The parallelization is performed on the elements of transdflist. Defaults to 1. - `showtime`: A logical value indicating if the duration of the function processing should be indicated before ending. Defaults to `FALSE`. - `verbose`: A logical flag indicating whether to print progress messages. Defaults to `TRUE`. ## Returns A data frame where each row corresponds to a transcript and contains the coordinates of the knee point and the maximum ECDF difference for each condition. ## Examples ```r exppath <- system.file("extdata", "exptab.csv", package="tepr") transpath <- system.file("extdata", "cugusi_6.tsv", package="tepr") expthres <- 0.1 ## Calculating necessary results expdf <- read.csv(exppath) transdf <- read.delim(transpath, header = FALSE) 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 kneeid reskneeid <- kneeid(bytranslistmean, expdf, verbose = FALSE) ```

kneeid function