#' Plot PCA run data from its components.

 #' @param colorBy The variable to color clusters by
 #' @param shape Shape of the points
 #' @param pcX User choice for the first principal component

 #' @param pcY User choice for the second principal component
 #' @param runPCA Run PCA if the reducedDimName does not exist. the Default is

 #' FALSE.

 #' @param inSCE Input \linkS4class{SingleCellExperiment} object.

 #' @param useAssay Indicate which assay to use. The default is "logcounts".
 #' @param reducedDimName a name to store the results of the dimension reduction
 #' coordinates obtained from this method. This is stored in the SingleCellExperiment
 #' object in the reducedDims slot. Required.

 #'

 #' @return A PCA plot

 #'

 #' @export

 #' @examples

 #' data("mouseBrainSubsetSCE")
 #' plotPCA(mouseBrainSubsetSCE, colorBy = "level1class",

 #'         reducedDimName = "PCA_counts")

 plotPCA <- function(inSCE, colorBy=NULL, shape=NULL, pcX="PC1",

                     pcY="PC2", reducedDimName="PCA", runPCA=FALSE,

                     useAssay="logcounts"){

   if(!(reducedDimName %in% names(SingleCellExperiment::reducedDims(inSCE)))){

     if (runPCA){

       inSCE <- scaterPCA(inSCE, useAssay = useAssay,

                       reducedDimName = reducedDimName)

     } else {

       stop(reducedDimName,

            " dimension not found. Run scaterPCA() or set runPCA to TRUE.")

     }

   }

   pcaDf <- data.frame(SingleCellExperiment::reducedDim(inSCE,

                                                        reducedDimName))
   if (!(pcX %in% colnames(pcaDf))){

     stop("pcX dimension ", pcX, " is not in the reducedDim data")
   }

   if (!(pcY %in% colnames(pcaDf))){

     stop("pcY dimension ", pcY, " is not in the reducedDim data")
   }

   # Need to add back in variances in the plot axis labels
   pcXlab <- pcX
   pcYlab <- pcY

   if (!is.null(colorBy)){

     pcaDf$color <- SingleCellExperiment::colData(inSCE)[, colorBy]

   }

   if (!is.null(shape)){

     pcaDf$shape <- factor(SingleCellExperiment::colData(inSCE)[, shape])

   }

   pcaDf$Sample <- colnames(inSCE)

   g <- ggplot2::ggplot(pcaDf, ggplot2::aes_string(pcX, pcY, label = "Sample")) +

     ggplot2::geom_point() +

     ggplot2::labs(x = pcXlab, y = pcYlab)

   if (!is.null(colorBy)){

     g <- g + ggplot2::aes_string(color = "color") +
       ggplot2::labs(color = colorBy)

   }

   if (!is.null(shape)){

     g <- g + ggplot2::aes_string(shape = "shape") +
       ggplot2::labs(shape = shape)

   }
   return(g)
 }