% Generated by roxygen2: do not edit by hand % Please edit documentation in R/ggPlotting.R \name{plotSCEDimReduceColData} \alias{plotSCEDimReduceColData} \title{Dimension reduction plot tool for colData} \usage{ plotSCEDimReduceColData( inSCE, sample = NULL, colorBy, groupBy = NULL, conditionClass = NULL, shape = NULL, reducedDimName = NULL, xlab = NULL, ylab = NULL, axisSize = 10, axisLabelSize = 10, dim1 = NULL, dim2 = NULL, bin = NULL, binLabel = NULL, dotSize = 2, transparency = 1, colorScale = NULL, colorLow = "white", colorMid = "gray", colorHigh = "blue", defaultTheme = TRUE, title = NULL, titleSize = 15, labelClusters = TRUE, legendTitle = NULL, legendTitleSize = 12, legendSize = 10, combinePlot = NULL, plotLabels = NULL ) } \arguments{ \item{inSCE}{Input \linkS4class{SingleCellExperiment} object with saved dimension reduction components or a variable with saved results. Required} \item{sample}{Character vector. Indicates which sample each cell belongs to.} \item{colorBy}{Color by a condition(any column of the annotation data). Required.} \item{groupBy}{Group by a condition(any column of the annotation data). Default NULL.} \item{conditionClass}{Class of the annotation data used in colorBy. Options are NULL, "factor" or "numeric". If NULL, class will default to the original class. Default NULL.} \item{shape}{Add shapes to each condition.} \item{reducedDimName}{Saved dimension reduction matrix name in the \linkS4class{SingleCellExperiment} object. Required.} \item{xlab}{Character vector. Label for x-axis. Default NULL.} \item{ylab}{Character vector. Label for y-axis. Default NULL.} \item{axisSize}{Size of x/y-axis ticks. Default 10.} \item{axisLabelSize}{Size of x/y-axis labels. Default 10.} \item{dim1}{1st dimension to be used for plotting. Can either be a string which specifies the name of the dimension to be plotted from reducedDims, or a numeric value which specifies the index of the dimension to be plotted. Default is NULL.} \item{dim2}{2nd dimension to be used for plotting. Can either be a string which specifies the name of the dimension to be plotted from reducedDims, or a numeric value which specifies the index of the dimension to be plotted. Default is NULL.} \item{bin}{Numeric vector. If single value, will divide the numeric values into the `bin` groups. If more than one value, will bin numeric values using values as a cut point.} \item{binLabel}{Character vector. Labels for the bins created by the `bin` parameter. Default NULL.} \item{dotSize}{Size of dots. Default 2.} \item{transparency}{Transparency of the dots, values will be 0-1. Default 1.} \item{colorScale}{Vector. Needs to be same length as the number of unique levels of colorBy. Will be used only if conditionClass = "factor" or "character". Default NULL.} \item{colorLow}{Character. A color available from `colors()`. The color will be used to signify the lowest values on the scale. Default 'white'.} \item{colorMid}{Character. A color available from `colors()`. The color will be used to signify the midpoint on the scale. Default 'gray'.} \item{colorHigh}{Character. A color available from `colors()`. The color will be used to signify the highest values on the scale. Default 'blue'.} \item{defaultTheme}{adds grid to plot when TRUE. Default TRUE.} \item{title}{Title of plot. Default NULL.} \item{titleSize}{Size of title of plot. Default 15.} \item{labelClusters}{Logical. Whether the cluster labels are plotted.} \item{legendTitle}{title of legend. Default NULL.} \item{legendTitleSize}{size of legend title. Default 12.} \item{legendSize}{size of legend. Default 10. Default FALSE.} \item{combinePlot}{Boolean. If multiple plots are generated (multiple samples, etc.), will combined plots using `cowplot::plot_grid`. Default TRUE.} \item{plotLabels}{labels to each plot. If set to "default", will use the name of the samples as the labels. If set to "none", no label will be plotted.} } \value{ a ggplot of the reduced dimensions. } \description{ Plot results of reduced dimensions data and colors by annotation data stored in the colData slot. } \examples{ plotSCEDimReduceColData( inSCE = mouseBrainSubsetSCE, colorBy = "tissue", shape = NULL, conditionClass = "factor", reducedDimName = "TSNE_counts", xlab = "tSNE1", ylab = "tSNE2", labelClusters = TRUE ) plotSCEDimReduceColData( inSCE = mouseBrainSubsetSCE, colorBy = "age", shape = NULL, conditionClass = "numeric", reducedDimName = "TSNE_counts", bin = c(-Inf, 20, 25, +Inf), xlab = "tSNE1", ylab = "tSNE2", labelClusters = FALSE ) }