R/gl.report.taglength.r

In dartR: Importing and Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis

#' @name gl.report.taglength
#' @title Reports summary of sequence tag length across loci
#' @description
#' SNP datasets generated by DArT typically have sequence tag lengths ranging
#' from 20 to 69 base pairs. This function reports summary statistics of the tag
#'  lengths.
#' @param x Name of the genlight object containing the SNP [required].
#' @param plot.out If TRUE, displays a plot to guide the decision on a filter
#' threshold [default TRUE].
#' @param plot_theme Theme for the plot. See Details for options
#' [default theme_dartR()].
#' @param plot_colors List of two color names for the borders and fill of the
#'  plots [default two_colors].
#' @param save2tmp If TRUE, saves any ggplots and listings to the session
#' temporary directory (tempdir) [default FALSE].
#' @param verbose Verbosity: 0, silent or fatal errors; 1, begin and end; 2,
#' progress log; 3, progress and results summary; 5, full report
#' [default 2, unless specified using gl.set.verbosity]
#'
#' @details The function \code{\link{gl.filter.taglength}} will filter out the
#'  loci with a tag length below a specified threshold.
#'
#' Quantiles are partitions of a finite set of values into q subsets of (nearly)
#' equal sizes. In this function q = 20. Quantiles are useful measures because
#' they are less susceptible to long-tailed distributions and outliers.
#'
#'\strong{ Function's output }
#'
#'  The minimum, maximum, mean and a tabulation of tag length quantiles against
#'  thresholds are provided. Output also includes a boxplot and a
#'  histogram to guide in the selection of a threshold for filtering on tag
#'  length.
#'
#'  Plots and table are saved to the temporal directory (tempdir) and can be
#'  accessed with the function \code{\link{gl.print.reports}} and listed with
#'  the function \code{\link{gl.list.reports}}. Note that they can be accessed
#'  only in the current R session because tempdir is cleared each time that the
#'  R session is closed.
#'
#'  Examples of other themes that can be used can be consulted in \itemize{
#'  \item \url{https://ggplot2.tidyverse.org/reference/ggtheme.html} and \item
#'  \url{https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/}
#'  }
#' @return Returns unaltered genlight object
#' @author Custodian: Arthur Georges -- Post to
#' \url{https://groups.google.com/d/forum/dartr}
#' @examples
#' out <- gl.report.taglength(testset.gl)
#' @seealso \code{\link{gl.filter.taglength}}, \code{\link{gl.list.reports}},
#'  \code{\link{gl.print.reports}}
#' @family report functions
#' @import patchwork
#' @export

gl.report.taglength <- function(x,
                                plot.out = TRUE,
                                plot_theme = theme_dartR(),
                                plot_colors = two_colors,
                                save2tmp = FALSE,
                                verbose = NULL) {
    # SET VERBOSITY
    verbose <- gl.check.verbosity(verbose)
    
    # FLAG SCRIPT START
    funname <- match.call()[[1]]
    utils.flag.start(func = funname,
                     build = "Jody",
                     verbosity = verbose)
    
    # CHECK DATATYPE
    datatype <- utils.check.datatype(x, verbose = verbose)
    
    # FUNCTION SPECIFIC ERROR CHECKING
    
    if (length(x@other$loc.metrics$TrimmedSequence) != nLoc(x)) {
        stop(
            error(
                "Fatal Error: Data must include Trimmed Sequences for each loci 
                in a column called 'TrimmedSequence' in the @other$loc.metrics
                slot.\n"
            )
        )
    }
    
    # DO THE JOB
    
    tags <- x@other$loc.metrics$TrimmedSequence
    nchar.tags <- nchar(as.character(tags))
    
    plot_tags <- data.frame(nchar.tags)
    colnames(plot_tags) <- "tags"
    
    # Boxplot
    p1 <-
        ggplot(plot_tags, aes(y = tags)) + 
      geom_boxplot(color = plot_colors[1], fill = plot_colors[2]) + 
      coord_flip() + plot_theme + xlim(range = c(-1,1)) + 
      ylim(0, 100) + ylab(" ") + 
      theme(axis.text.y = element_blank(), axis.ticks.y = element_blank()) + 
      ggtitle("SNP data - Tag Length")
    
    # Histogram
    p2 <-
        ggplot(plot_tags, aes(x = tags)) + 
      geom_histogram(bins = 50,color = plot_colors[1], fill = plot_colors[2]) + 
      coord_cartesian(xlim = c(0,100)) + 
      xlab("Tag Length") + 
      ylab("Count") + 
      plot_theme
    
    # Print out some statistics
    stats <- summary(nchar.tags)
    cat("  Reporting Tag Length\n")
    cat("  No. of loci =", nLoc(x), "\n")
    cat("  No. of individuals =", nInd(x), "\n")
    cat("    Minimum      : ", stats[1], "\n")
    cat("    1st quantile : ", stats[2], "\n")
    cat("    Median       : ", stats[3], "\n")
    cat("    Mean         : ", stats[4], "\n")
    cat("    3r quantile  : ", stats[5], "\n")
    cat("    Maximum      : ", stats[6], "\n")
    cat("    Missing Rate Overall: ", round(sum(is.na(as.matrix(
        x
    ))) / (nLoc(x) * nInd(x)), 2), "\n\n")
    
    # Determine the loss of loci for a given threshold using quantiles
    quantile_res <-
        quantile(nchar.tags, probs = seq(0, 1, 1 / 20),type=1)
    retained <- unlist(lapply(quantile_res, function(y) {
        res <- length(nchar.tags[nchar.tags >= y])
    }))
    pc.retained <- round(retained * 100 / nLoc(x), 1)
    filtered <- nLoc(x) - retained
    pc.filtered <- 100 - pc.retained
    df <-
        data.frame(as.numeric(sub("%", "", names(quantile_res))),
                   quantile_res,
                   retained,
                   pc.retained,
                   filtered,
                   pc.filtered)
    colnames(df) <-
        c("Quantile",
          "Threshold",
          "Retained",
          "Percent",
          "Filtered",
          "Percent")
    df <- df[order(-df$Quantile), ]
    df$Quantile <- paste0(df$Quantile, "%")
    rownames(df) <- NULL
    
    # PRINTING OUTPUTS
    if (plot.out) {
        # using package patchwork
        p3 <- (p1 / p2) + plot_layout(heights = c(1, 4))
        print(p3)
    }
    print(df)
    
    # SAVE INTERMEDIATES TO TEMPDIR
    
    # creating temp file names
    if (save2tmp) {
        if (plot.out) {
            temp_plot <- tempfile(pattern = "Plot_")
            match_call <-
                paste0(names(match.call()),
                       "_",
                       as.character(match.call()),
                       collapse = "_")
            # saving to tempdir
            saveRDS(list(match_call, p3), file = temp_plot)
            if (verbose >= 2) {
                cat(report("  Saving the ggplot to session tempfile\n"))
            }
        }
        temp_table <- tempfile(pattern = "Table_")
        saveRDS(list(match_call, df), file = temp_table)
        if (verbose >= 2) {
            cat(report("  Saving tabulation to session tempfile\n"))
            cat(
                report(
                    "  NOTE: Retrieve output files from tempdir using 
                    gl.list.reports() and gl.print.reports()\n"
                )
            )
        }
    }
    
    # FLAG SCRIPT END
    
    if (verbose >= 1) {
        cat(report("Completed:", funname, "\n"))
    }
    
    # RETURN
    invisible(x)
    
}