R/plotQC.R

In Liubuntu/SeqSQC: A bioconductor package for sample quality check with next generation sequencing data

#' Plot the QC results for specific QC steps. 
#' 
#' Plot QC results.
#' @param seqfile SeqSQC object with QC results.
#' @param QCstep which QC step the user want to do plotting. Takes
#'     values of \code{c("MissingRate", "SexCheck", "Inbreeding",
#'     "IBD", "PCA")}
#' @param interactive whether to generate interactive plot. Recommend
#'     to use \code{interactive = TRUE} if user perform sample QC
#'     using an rmarkdown script and output plot to html format.
#' @param sdcoef for inbreeding outlier check, how many standard
#'     deviation we need for identification of inbreeding
#'     outliers. The default is 5.
#' @param pc1 the eigenvector on x axis for PCA result. The default is
#'     "EV1" for eigenvector 1.
#' @param pc2 the eigenvector on y axis for PCA result. The default is
#'     "EV2" for eigenvector 2.
#' @param pairedScatter for PCA result, whether to plot the paired
#'     scatterplot for the first 4 PC axes.
#' @param ... Arguments to be passed to other methods.
#' @import ggplot2
#' @import RColorBrewer
#' @import GGally
#' @import plotly
#' @export
#' @return the ggplot or interactive plot (if output is in html
#'     format) for specific QC result. If "interactive=FALSE", it
#'     returns a ggplot and author could have the flexibility to add
#'     on any layers, scales, faceting specifications and coordinate
#'     systems.
#' @examples
#' load(system.file("extdata", "example.seqfile.Rdata", package="SeqSQC"))
#' gfile <- system.file("extdata", "example.gds", package="SeqSQC")
#' seqfile <- SeqSQC(gdsfile = gfile, QCresult = QCresult(seqfile))
#' p <- plotQC(seqfile, QCstep="PCA", interactive=FALSE)
#' p
#' @author Qian Liu \email{qliu7@buffalo.edu}

plotQC <- function(seqfile,
                   QCstep=c("MissingRate", "SexCheck", "Inbreeding", "IBD", "PCA"),
                   interactive=FALSE, sdcoef=5, pc1="EV1", pc2="EV2",
                   pairedScatter=FALSE, ...){

    res.qc <- plotQCData(seqfile, QCstep = QCstep)

    ## plotting
    QCstep <- match.arg(QCstep)
    
    if(QCstep == "MissingRate"){
        p <- plotMissingRate(res.qc, interactive = interactive)
    }else if(QCstep == "SexCheck"){
        p <- plotSexCheck(res.qc, interactive = interactive)
    }else if(QCstep == "Inbreeding"){
        p <- plotInbreeding(res.qc, interactive = interactive, sdcoef = sdcoef)
    }else if(QCstep == "IBD"){
        p <- plotIBD(res.qc, interactive = interactive)
    }else if(QCstep == "PCA"){
     p <- plotPop(res.qc, interactive = interactive, ...)
    }
    return(p)
}