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Commit c554dc43 authored by l.zappia's avatar l.zappia
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Merge branch 'master' into devel 

* master:
  Version 0.99.14
  Add panel function to vignette
  Change var plot scale
  Run checks
  Update panel functions
  Add makeOverallPanel function
  Add makeDiffPanel function
  Add options to comparison plots

From: Luke Zappia <lazappi@users.noreply.github.com>

git-svn-id: https://hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/splatter@127789 bc3139a8-67e5-0310-9ffc-ced21a209358
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DESCRIPTION
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Package: splatter Package: splatter
Type: Package Type: Package
Title: Simple Simulation of Single-cell RNA Sequencing Data Title: Simple Simulation of Single-cell RNA Sequencing Data
Version: 0.99.13 Version: 0.99.14
Date: 2017-03-25 Date: 2017-03-28
Author: Luke Zappia Author: Luke Zappia
Authors@R: Authors@R:
c(person("Luke", "Zappia", role = c("aut", "cre"), c(person("Luke", "Zappia", role = c("aut", "cre"),
...@@ -46,7 +46,8 @@ Suggests: ...@@ -46,7 +46,8 @@ Suggests:
BiocStyle, BiocStyle,
covr, covr,
S4Vectors, S4Vectors,
SummarizedExperiment SummarizedExperiment,
cowplot
biocViews: SingleCell, RNASeq, Transcriptomics, GeneExpression, Sequencing, biocViews: SingleCell, RNASeq, Transcriptomics, GeneExpression, Sequencing,
Software Software
URL: https://github.com/Oshlack/splatter URL: https://github.com/Oshlack/splatter
......
NAMESPACE
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...@@ -20,6 +20,9 @@ export(lun2Estimate) ...@@ -20,6 +20,9 @@ export(lun2Estimate)
export(lun2Simulate) export(lun2Simulate)
export(lunEstimate) export(lunEstimate)
export(lunSimulate) export(lunSimulate)
export(makeCompPanel)
export(makeDiffPanel)
export(makeOverallPanel)
export(newLun2Params) export(newLun2Params)
export(newLunParams) export(newLunParams)
export(newSCDDParams) export(newSCDDParams)
...@@ -58,17 +61,20 @@ importFrom(checkmate,checkIntegerish) ...@@ -58,17 +61,20 @@ importFrom(checkmate,checkIntegerish)
importFrom(checkmate,checkNumber) importFrom(checkmate,checkNumber)
importFrom(checkmate,checkNumeric) importFrom(checkmate,checkNumeric)
importFrom(ggplot2,aes_string) importFrom(ggplot2,aes_string)
importFrom(ggplot2,element_blank)
importFrom(ggplot2,geom_abline) importFrom(ggplot2,geom_abline)
importFrom(ggplot2,geom_boxplot) importFrom(ggplot2,geom_boxplot)
importFrom(ggplot2,geom_hline) importFrom(ggplot2,geom_hline)
importFrom(ggplot2,geom_point) importFrom(ggplot2,geom_point)
importFrom(ggplot2,geom_smooth) importFrom(ggplot2,geom_smooth)
importFrom(ggplot2,geom_violin)
importFrom(ggplot2,ggplot) importFrom(ggplot2,ggplot)
importFrom(ggplot2,ggtitle) importFrom(ggplot2,ggtitle)
importFrom(ggplot2,scale_colour_manual)
importFrom(ggplot2,scale_fill_manual)
importFrom(ggplot2,scale_x_log10) importFrom(ggplot2,scale_x_log10)
importFrom(ggplot2,scale_y_continuous) importFrom(ggplot2,scale_y_continuous)
importFrom(ggplot2,scale_y_log10) importFrom(ggplot2,scale_y_log10)
importFrom(ggplot2,theme)
importFrom(ggplot2,theme_minimal) importFrom(ggplot2,theme_minimal)
importFrom(ggplot2,xlab) importFrom(ggplot2,xlab)
importFrom(ggplot2,ylab) importFrom(ggplot2,ylab)
......
NEWS.md
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# 0.99.14
* Add functions for making comparison panels
* Add panel section to vignette
* Change variance plot scale (for consistency)
# 0.99.13 # 0.99.13
* Modify how Lun2Params stores gene paramters to use data.frame * Modify how Lun2Params stores gene paramters to use data.frame
......
R/compare.R
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...@@ -4,6 +4,10 @@ ...@@ -4,6 +4,10 @@
#' comparing them. #' comparing them.
#' #'
#' @param sces named list of SCESet objects to combine and compare. #' @param sces named list of SCESet objects to combine and compare.
#' @param point.size size of points in scatter plots.
#' @param point.alpha opacity of points in scatter plots.
#' @param fits whether to include fits in scatter plots.
#' @param colours vector of colours to use for each dataset.
#' #'
#' @details #' @details
#' The returned list has three items: #' The returned list has three items:
...@@ -44,14 +48,25 @@ ...@@ -44,14 +48,25 @@
#' names(comparison) #' names(comparison)
#' names(comparison$Plots) #' names(comparison$Plots)
#' @importFrom ggplot2 ggplot aes_string geom_point geom_smooth geom_boxplot #' @importFrom ggplot2 ggplot aes_string geom_point geom_smooth geom_boxplot
#' geom_violin scale_y_continuous scale_y_log10 scale_x_log10 xlab ylab ggtitle #' scale_y_continuous scale_y_log10 scale_x_log10 xlab ylab ggtitle
#' theme_minimal #' theme_minimal scale_colour_manual scale_fill_manual
#' @importFrom scater cpm<- #' @importFrom scater cpm<-
#' @export #' @export
compareSCESets <- function(sces) { compareSCESets <- function(sces, point.size = 0.1, point.alpha = 0.1,
fits = TRUE, colours = NULL) {
checkmate::assertList(sces, types = "SCESet", any.missing = FALSE, checkmate::assertList(sces, types = "SCESet", any.missing = FALSE,
min.len = 1, names = "unique") min.len = 1, names = "unique")
checkmate::assertNumber(point.size, finite = TRUE)
checkmate::assertNumber(point.alpha, lower = 0, upper = 1)
checkmate::assertLogical(fits, any.missing = FALSE, len = 1)
if (!is.null(colours)) {
checkmate::assertCharacter(colours, any.missing = FALSE,
len = length(sces))
} else {
colours <- scales::hue_pal()(length(sces))
}
for (name in names(sces)) { for (name in names(sces)) {
sce <- sces[[name]] sce <- sces[[name]]
...@@ -84,25 +99,27 @@ compareSCESets <- function(sces) { ...@@ -84,25 +99,27 @@ compareSCESets <- function(sces) {
colour = "Dataset")) + colour = "Dataset")) +
#geom_violin(draw_quantiles = c(0.25, 0.5, 0.75)) + #geom_violin(draw_quantiles = c(0.25, 0.5, 0.75)) +
geom_boxplot() + geom_boxplot() +
scale_colour_manual(values = colours) +
ylab(expression(paste("Mean ", log[2], "(CPM + 1)"))) + ylab(expression(paste("Mean ", log[2], "(CPM + 1)"))) +
ggtitle("Distribution of mean expression") + ggtitle("Distribution of mean expression") +
theme_minimal() theme_minimal()
vars <- ggplot(fData.all, vars <- ggplot(fData.all,
aes_string(x = "Dataset", y = "VarCPM", aes_string(x = "Dataset", y = "VarLogCPM",
colour = "Dataset")) + colour = "Dataset")) +
#geom_violin(draw_quantiles = c(0.25, 0.5, 0.75)) + #geom_violin(draw_quantiles = c(0.25, 0.5, 0.75)) +
geom_boxplot() + geom_boxplot() +
scale_y_log10(labels = scales::comma) + scale_colour_manual(values = colours) +
ylab("CPM Variance") + ylab(expression(paste("Variance ", log[2], "(CPM + 1)"))) +
ggtitle("Distribution of variance") + ggtitle("Distribution of variance") +
theme_minimal() theme_minimal()
mean.var <- ggplot(fData.all, mean.var <- ggplot(fData.all,
aes_string(x = "MeanLogCPM", y = "VarLogCPM", aes_string(x = "MeanLogCPM", y = "VarLogCPM",
colour = "Dataset", fill = "Dataset")) + colour = "Dataset", fill = "Dataset")) +
geom_point(size = 0.1, alpha = 0.1) + geom_point(size = point.size, alpha = point.alpha) +
geom_smooth() + scale_colour_manual(values = colours) +
scale_fill_manual(values = colours) +
xlab(expression(paste("Mean ", log[2], "(CPM + 1)"))) + xlab(expression(paste("Mean ", log[2], "(CPM + 1)"))) +
ylab(expression(paste("Variance ", log[2], "(CPM + 1)"))) + ylab(expression(paste("Variance ", log[2], "(CPM + 1)"))) +
ggtitle("Mean-variance relationship") + ggtitle("Mean-variance relationship") +
...@@ -113,6 +130,7 @@ compareSCESets <- function(sces) { ...@@ -113,6 +130,7 @@ compareSCESets <- function(sces) {
colour = "Dataset")) + colour = "Dataset")) +
geom_boxplot() + geom_boxplot() +
scale_y_continuous(labels = scales::comma) + scale_y_continuous(labels = scales::comma) +
scale_colour_manual(values = colours) +
ylab("Total counts per cell") + ylab("Total counts per cell") +
ggtitle("Distribution of library sizes") + ggtitle("Distribution of library sizes") +
theme_minimal() theme_minimal()
...@@ -122,6 +140,7 @@ compareSCESets <- function(sces) { ...@@ -122,6 +140,7 @@ compareSCESets <- function(sces) {
colour = "Dataset")) + colour = "Dataset")) +
geom_boxplot() + geom_boxplot() +
scale_y_continuous(limits = c(0, 100)) + scale_y_continuous(limits = c(0, 100)) +
scale_colour_manual(values = colours) +
ylab("Percentage zeros per gene") + ylab("Percentage zeros per gene") +
ggtitle("Distribution of zeros per gene") + ggtitle("Distribution of zeros per gene") +
theme_minimal() theme_minimal()
...@@ -131,6 +150,7 @@ compareSCESets <- function(sces) { ...@@ -131,6 +150,7 @@ compareSCESets <- function(sces) {
colour = "Dataset")) + colour = "Dataset")) +
geom_boxplot() + geom_boxplot() +
scale_y_continuous(limits = c(0, 100)) + scale_y_continuous(limits = c(0, 100)) +
scale_colour_manual(values = colours) +
ylab("Percentage zeros per cell") + ylab("Percentage zeros per cell") +
ggtitle("Distribution of zeros per cell") + ggtitle("Distribution of zeros per cell") +
theme_minimal() theme_minimal()
...@@ -138,14 +158,20 @@ compareSCESets <- function(sces) { ...@@ -138,14 +158,20 @@ compareSCESets <- function(sces) {
mean.zeros <- ggplot(fData.all, mean.zeros <- ggplot(fData.all,
aes_string(x = "MeanCounts", y = "pct_dropout", aes_string(x = "MeanCounts", y = "pct_dropout",
colour = "Dataset", fill = "Dataset")) + colour = "Dataset", fill = "Dataset")) +
geom_point(size = 0.1, alpha = 0.1) + geom_point(size = point.size, alpha = point.alpha) +
geom_smooth() +
scale_x_log10(labels = scales::comma) + scale_x_log10(labels = scales::comma) +
scale_colour_manual(values = colours) +
scale_fill_manual(values = colours) +
xlab("Mean count") + xlab("Mean count") +
ylab("Percentage zeros") + ylab("Percentage zeros") +
ggtitle("Mean-dropout relationship") + ggtitle("Mean-dropout relationship") +
theme_minimal() theme_minimal()
if (fits) {
mean.var <- mean.var + geom_smooth()
mean.zeros <- mean.zeros + geom_smooth()
}
comparison <- list(FeatureData = fData.all, comparison <- list(FeatureData = fData.all,
PhenoData = pData.all, PhenoData = pData.all,
Plots = list(Means = means, Plots = list(Means = means,
...@@ -166,6 +192,10 @@ compareSCESets <- function(sces) { ...@@ -166,6 +192,10 @@ compareSCESets <- function(sces) {
#' #'
#' @param sces named list of SCESet objects to combine and compare. #' @param sces named list of SCESet objects to combine and compare.
#' @param ref string giving the name of the SCESet to use as the reference #' @param ref string giving the name of the SCESet to use as the reference
#' @param point.size size of points in scatter plots.
#' @param point.alpha opacity of points in scatter plots.
#' @param fits whether to include fits in scatter plots.
#' @param colours vector of colours to use for each dataset.
#' #'
#' @details #' @details
#' #'
...@@ -225,19 +255,31 @@ compareSCESets <- function(sces) { ...@@ -225,19 +255,31 @@ compareSCESets <- function(sces) {
#' names(difference) #' names(difference)
#' names(difference$Plots) #' names(difference$Plots)
#' @importFrom ggplot2 ggplot aes_string geom_point geom_boxplot xlab ylab #' @importFrom ggplot2 ggplot aes_string geom_point geom_boxplot xlab ylab
#' ggtitle theme_minimal geom_hline geom_abline #' ggtitle theme_minimal geom_hline geom_abline scale_colour_manual
#' scale_fill_manual
#' @importFrom scater cpm<- #' @importFrom scater cpm<-
#' @export #' @export
diffSCESets <- function(sces, ref) { diffSCESets <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
fits = TRUE, colours = NULL) {
checkmate::assertList(sces, types = "SCESet", any.missing = FALSE, checkmate::assertList(sces, types = "SCESet", any.missing = FALSE,
min.len = 2, names = "unique") min.len = 2, names = "unique")
checkmate::assertString(ref) checkmate::assertString(ref)
checkmate::assertNumber(point.size, finite = TRUE)
checkmate::assertNumber(point.alpha, lower = 0, upper = 1)
checkmate::assertLogical(fits, any.missing = FALSE, len = 1)
if (!(ref %in% names(sces))) { if (!(ref %in% names(sces))) {
stop("'ref' must be the name of an SCESet in 'sces'") stop("'ref' must be the name of an SCESet in 'sces'")
} }
if (!is.null(colours)) {
checkmate::assertCharacter(colours, any.missing = FALSE,
len = length(sces) - 1)
} else {
colours <- scales::hue_pal()(length(sces))
}
ref.dim <- dim(sces[[ref]]) ref.dim <- dim(sces[[ref]])
for (name in names(sces)) { for (name in names(sces)) {
...@@ -314,6 +356,7 @@ diffSCESets <- function(sces, ref) { ...@@ -314,6 +356,7 @@ diffSCESets <- function(sces, ref) {
colour = "Dataset")) + colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_boxplot() + geom_boxplot() +
scale_colour_manual(values = colours) +
ylab(expression(paste("Rank difference mean ", log[2], "(CPM + 1)"))) + ylab(expression(paste("Rank difference mean ", log[2], "(CPM + 1)"))) +
ggtitle("Difference in mean expression") + ggtitle("Difference in mean expression") +
theme_minimal() theme_minimal()
...@@ -323,6 +366,7 @@ diffSCESets <- function(sces, ref) { ...@@ -323,6 +366,7 @@ diffSCESets <- function(sces, ref) {
colour = "Dataset")) + colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_boxplot() + geom_boxplot() +
scale_colour_manual(values = colours) +
ylab(expression(paste("Rank difference variance ", log[2], ylab(expression(paste("Rank difference variance ", log[2],
"(CPM + 1)"))) + "(CPM + 1)"))) +
ggtitle("Difference in variance") + ggtitle("Difference in variance") +
...@@ -330,9 +374,11 @@ diffSCESets <- function(sces, ref) { ...@@ -330,9 +374,11 @@ diffSCESets <- function(sces, ref) {
mean.var <- ggplot(fData.all, mean.var <- ggplot(fData.all,
aes_string(x = "exprs_rank", y = "MeanRankVarDiff", aes_string(x = "exprs_rank", y = "MeanRankVarDiff",
colour = "Dataset")) + colour = "Dataset", fill = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
scale_fill_manual(values = colours) +
xlab("Expression rank") + xlab("Expression rank") +
ylab(expression(paste("Difference in variance ", log[2], ylab(expression(paste("Difference in variance ", log[2],
"(CPM + 1)"))) + "(CPM + 1)"))) +
...@@ -344,6 +390,7 @@ diffSCESets <- function(sces, ref) { ...@@ -344,6 +390,7 @@ diffSCESets <- function(sces, ref) {
colour = "Dataset")) + colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_boxplot() + geom_boxplot() +
scale_colour_manual(values = colours) +
ylab(paste("Rank difference libray size")) + ylab(paste("Rank difference libray size")) +
ggtitle("Difference in library sizes") + ggtitle("Difference in library sizes") +
theme_minimal() theme_minimal()
...@@ -353,6 +400,7 @@ diffSCESets <- function(sces, ref) { ...@@ -353,6 +400,7 @@ diffSCESets <- function(sces, ref) {
colour = "Dataset")) + colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_boxplot() + geom_boxplot() +
scale_colour_manual(values = colours) +
ylab(paste("Rank difference percentage zeros")) + ylab(paste("Rank difference percentage zeros")) +
ggtitle("Difference in zeros per gene") + ggtitle("Difference in zeros per gene") +
theme_minimal() theme_minimal()
...@@ -362,15 +410,18 @@ diffSCESets <- function(sces, ref) { ...@@ -362,15 +410,18 @@ diffSCESets <- function(sces, ref) {
colour = "Dataset")) + colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_boxplot() + geom_boxplot() +
scale_colour_manual(values = colours) +
ylab(paste("Rank difference percentage zeros")) + ylab(paste("Rank difference percentage zeros")) +
ggtitle("Difference in zeros per cell") + ggtitle("Difference in zeros per cell") +
theme_minimal() theme_minimal()
mean.zeros <- ggplot(fData.all, mean.zeros <- ggplot(fData.all,
aes_string(x = "exprs_rank", y = "MeanRankZerosDiff", aes_string(x = "exprs_rank", y = "MeanRankZerosDiff",
colour = "Dataset")) + colour = "Dataset", fill = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") + geom_hline(yintercept = 0, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
scale_fill_manual(values = colours) +
xlab("Expression rank") + xlab("Expression rank") +
ylab("Difference in percentage zeros per gene") + ylab("Difference in percentage zeros per gene") +
ggtitle("Difference in mean-zeros relationship") + ggtitle("Difference in mean-zeros relationship") +
...@@ -380,7 +431,8 @@ diffSCESets <- function(sces, ref) { ...@@ -380,7 +431,8 @@ diffSCESets <- function(sces, ref) {
aes_string(x = "RefRankMeanLogCPM", y = "MeanLogCPM", aes_string(x = "RefRankMeanLogCPM", y = "MeanLogCPM",
colour = "Dataset")) + colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") + geom_abline(intercept = 0, slope = 1, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
xlab(expression(paste("Reference mean ", log[2], "(CPM + 1)"))) + xlab(expression(paste("Reference mean ", log[2], "(CPM + 1)"))) +
ylab(expression(paste("Alternative mean ", log[2], "(CPM + 1)"))) + ylab(expression(paste("Alternative mean ", log[2], "(CPM + 1)"))) +
ggtitle("Ranked means") + ggtitle("Ranked means") +
...@@ -390,7 +442,8 @@ diffSCESets <- function(sces, ref) { ...@@ -390,7 +442,8 @@ diffSCESets <- function(sces, ref) {
aes_string(x = "RefRankVarLogCPM", y = "VarLogCPM", aes_string(x = "RefRankVarLogCPM", y = "VarLogCPM",
colour = "Dataset")) + colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") + geom_abline(intercept = 0, slope = 1, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
xlab(expression(paste("Reference variance ", log[2], "(CPM + 1)"))) + xlab(expression(paste("Reference variance ", log[2], "(CPM + 1)"))) +
ylab(expression(paste("Alternative variance ", log[2], "(CPM + 1)"))) + ylab(expression(paste("Alternative variance ", log[2], "(CPM + 1)"))) +
ggtitle("Ranked variances") + ggtitle("Ranked variances") +
...@@ -400,7 +453,8 @@ diffSCESets <- function(sces, ref) { ...@@ -400,7 +453,8 @@ diffSCESets <- function(sces, ref) {
aes_string(x = "RefRankLibSize", y = "total_counts", aes_string(x = "RefRankLibSize", y = "total_counts",
colour = "Dataset")) + colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") + geom_abline(intercept = 0, slope = 1, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
xlab("Reference library size") + xlab("Reference library size") +
ylab("Alternative library size") + ylab("Alternative library size") +
ggtitle("Ranked library sizes") + ggtitle("Ranked library sizes") +
...@@ -410,7 +464,8 @@ diffSCESets <- function(sces, ref) { ...@@ -410,7 +464,8 @@ diffSCESets <- function(sces, ref) {
aes_string(x = "RefRankZeros", y = "pct_dropout", aes_string(x = "RefRankZeros", y = "pct_dropout",
colour = "Dataset")) + colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") + geom_abline(intercept = 0, slope = 1, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
xlab("Reference percentage zeros") + xlab("Reference percentage zeros") +
ylab("Alternative percentage zeros") + ylab("Alternative percentage zeros") +
ggtitle("Ranked percentage zeros per gene") + ggtitle("Ranked percentage zeros per gene") +
...@@ -420,12 +475,18 @@ diffSCESets <- function(sces, ref) { ...@@ -420,12 +475,18 @@ diffSCESets <- function(sces, ref) {
aes_string(x = "RefRankZeros", y = "pct_dropout", aes_string(x = "RefRankZeros", y = "pct_dropout",
colour = "Dataset")) + colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") + geom_abline(intercept = 0, slope = 1, colour = "red") +
geom_point() + geom_point(size = point.size, alpha = point.alpha) +
scale_colour_manual(values = colours) +
xlab("Reference percentage zeros") + xlab("Reference percentage zeros") +
ylab("Alternative percentage zeros") + ylab("Alternative percentage zeros") +
ggtitle("Ranked percentage zeros per cell") + ggtitle("Ranked percentage zeros per cell") +
theme_minimal() theme_minimal()
if (fits) {
mean.var <- mean.var + geom_smooth()
mean.zeros <- mean.zeros + geom_smooth()
}
comparison <- list(Reference = ref.sce, comparison <- list(Reference = ref.sce,
FeatureData = fData.all, FeatureData = fData.all,
PhenoData = pData.all, PhenoData = pData.all,
...@@ -444,3 +505,282 @@ diffSCESets <- function(sces, ref) { ...@@ -444,3 +505,282 @@ diffSCESets <- function(sces, ref) {
return(comparison) return(comparison)
} }
#' Make comparison panel
#'
#' Combine the plots from \code{compareSCESets} into a single panel.
#'
#' @param comp list returned by \code{\link{compareSCESets}}.
#' @param title title for the panel.
#' @param labels vector of labels for each of the seven plots.
#'
#' @return Combined panel plot
#'
#' @examples
#' \dontrun{
#' sim1 <- splatSimulate(nGenes = 1000, groupCells = 20)
#' sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
#' comparison <- compareSCESets(list(Splat = sim1, Simple = sim2))
#' panel <- makeCompPanel(comparison)
#' }
#'
#' @importFrom ggplot2 theme element_blank
#' @export
makeCompPanel <- function(comp, title = "Comparison",
labels = c("Means", "Variance",
"Mean-variance relationship",
"Library size", "Zeros per gene",
"Zeros per cell",
"Mean-zeros relationship")) {
if (!requireNamespace("cowplot", quietly = TRUE)) {
stop("The `cowplot` package is required to make panels.")
}
checkmate::assertList(comp, any.missing = FALSE, len = 3)
checkmate::checkString(title)
checkmate::checkCharacter(labels, len = 7)
plots <- list(p1 = comp$Plots$Means, p2 = comp$Plots$Variances,
p3 = comp$Plots$MeanVar, p4 = comp$Plots$LibrarySizes,
p5 = comp$Plots$ZerosGene, p6 = comp$Plots$ZerosCell,
p7 = comp$Plots$MeanZeros)
# Remove titles and legends
for (plot in names(plots)) {
plots[[plot]] <- plots[[plot]] + theme(legend.position = "none",
plot.title = element_blank())
}
# Remove x-axis title from some plots
for (plot in paste0("p", c(1, 2, 4, 5, 6))) {
plots[[plot]] <- plots[[plot]] + theme(axis.title.x = element_blank())
}
plots$leg <- cowplot::get_legend(plots$p1 +
theme(legend.position = "bottom"))
panel <- cowplot::ggdraw() +
cowplot::draw_label(title, 0.5, 0.98,
fontface = "bold", size = 18) +
cowplot::draw_label(labels[1], 0.01, 0.95,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p1, 0.0, 0.74, 0.5, 0.20) +
cowplot::draw_label(labels[2], 0.51, 0.95,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p2, 0.5, 0.74, 0.5, 0.20) +
cowplot::draw_label(labels[3], 0.01, 0.70,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p3, 0.0, 0.49, 0.5, 0.20) +
cowplot::draw_label(labels[4], 0.51, 0.70,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p4, 0.5, 0.49, 0.5, 0.20) +
cowplot::draw_label(labels[5], 0.01, 0.45,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p5, 0.0, 0.24, 0.5, 0.20) +
cowplot::draw_label(labels[6], 0.51, 0.45,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p6, 0.5, 0.24, 0.5, 0.20) +
cowplot::draw_label(labels[7], 0.01, 0.21,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p7, 0.0, 0.00, 0.5, 0.20) +
cowplot::draw_plot(plots$leg, 0.5, 0.00, 0.5, 0.20)
return(panel)
}
#' Make difference panel
#'
#' Combine the plots from \code{diffSCESets} into a single panel.
#'
#' @param diff list returned by \code{\link{diffSCESets}}.
#' @param title title for the panel.
#' @param labels vector of labels for each of the seven sections.
#'
#' @return Combined panel plot
#'
#' @examples
#' \dontrun{
#' sim1 <- splatSimulate(nGenes = 1000, groupCells = 20)
#' sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
#' difference <- diffSCESets(list(Splat = sim1, Simple = sim2), ref = "Simple")
#' panel <- makeDiffPanel(difference)
#' }
#'
#' @importFrom ggplot2 theme element_blank
#' @export
makeDiffPanel <- function(diff, title = "Difference comparison",
labels = c("Means", "Variance", "Library size",
"Zeros per cell", "Zeros per gene",
"Mean-variance relationship",
"Mean-zeros relationship")) {
if (!requireNamespace("cowplot", quietly = TRUE)) {
stop("The `cowplot` package is required to make panels.")
}
checkmate::assertList(diff, any.missing = FALSE, len = 5)
checkmate::checkString(title)
checkmate::checkCharacter(labels, len = 7)
plots <- list(p1 = diff$Plots$Means, p2 = diff$QQPlots$Means,
p3 = diff$Plots$Variances, p4 = diff$QQPlots$Variances,
p5 = diff$Plots$MeanVar, p6 = diff$Plots$LibrarySizes,
p7 = diff$QQPlots$LibrarySizes, p8 = diff$Plots$ZerosCell,
p9 = diff$QQPlots$ZerosCell, p10 = diff$Plots$ZerosGene,
p11 = diff$QQPlots$ZerosGene, p12 = diff$Plots$MeanZeros)
# Remove titles and legends
for (plot in names(plots)) {
plots[[plot]] <- plots[[plot]] + theme(legend.position = "none",
plot.title = element_blank())
}
# Remove x-axis title from some plots
for (plot in paste0("p", c(1, 3, 6, 8, 10))) {
plots[[plot]] <- plots[[plot]] + theme(axis.title.x = element_blank())
}
plots$leg <- cowplot::get_legend(plots$p1 +
theme(legend.position = "bottom"))
panel <- cowplot::ggdraw() +
cowplot::draw_label(title, 0.5, 0.98,
fontface = "bold", size = 18) +
cowplot::draw_label(labels[1], 0.0, 0.94,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p1, 0.0, 0.64, 0.18, 0.29) +
cowplot::draw_plot(plots$p2, 0.0, 0.32, 0.18, 0.29) +
cowplot::draw_label(labels[2], 0.21, 0.94,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p3, 0.21, 0.64, 0.18, 0.29) +
cowplot::draw_plot(plots$p4, 0.21, 0.32, 0.18, 0.29) +
cowplot::draw_label(labels[6], 0.0, 0.30,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p5, 0.0, 0.0, 0.38, 0.29) +
cowplot::draw_label(labels[3], 0.41, 0.94,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p6, 0.41, 0.64, 0.18, 0.29) +
cowplot::draw_plot(plots$p7, 0.41, 0.32, 0.18, 0.29) +
cowplot::draw_label(labels[4], 0.61, 0.94,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p8, 0.61, 0.64, 0.18, 0.29) +
cowplot::draw_plot(plots$p9, 0.61, 0.32, 0.18, 0.29) +
cowplot::draw_label(labels[7], 0.41, 0.30,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p12, 0.41, 0.0, 0.38, 0.29) +
cowplot::draw_label(labels[5], 0.81, 0.94,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p10, 0.81, 0.64, 0.18, 0.29) +
cowplot::draw_plot(plots$p11, 0.81, 0.32, 0.18, 0.29) +
cowplot::draw_plot(plots$leg, 0.81, 0.0, 0.2, 0.29)
return(panel)
}
#' Make overall panel
#'
#' Combine the plots from \code{compSCESets} and \code{diffSCESets} into a
#' single panel.
#'
#' @param comp list returned by \code{\link{compareSCESets}}.
#' @param diff list returned by \code{\link{diffSCESets}}.
#' @param title title for the panel.
#' @param row.labels vector of labels for each of the seven rows.
#'
#' @return Combined panel plot
#'
#' @examples
#' \dontrun{
#' sim1 <- splatSimulate(nGenes = 1000, groupCells = 20)
#' sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
#' comparison <- compSCESets(list(Splat = sim1, Simple = sim2))
#' difference <- diffSCESets(list(Splat = sim1, Simple = sim2), ref = "Simple")
#' panel <- makeOverallPanel(comparison, difference)
#' }
#'
#' @importFrom ggplot2 theme element_blank
#' @export
makeOverallPanel <- function(comp, diff, title = "Overall comparison",
row.labels = c("Means", "Variance",
"Mean-variance relationship",
"Library size", "Zeros per cell",
"Zeros per gene",
"Mean-zeros relationship")) {
if (!requireNamespace("cowplot", quietly = TRUE)) {
stop("The `cowplot` package is required to make panels.")
}
checkmate::assertList(comp, any.missing = FALSE, len = 3)
checkmate::assertList(diff, any.missing = FALSE, len = 5)
checkmate::checkString(title)
checkmate::checkCharacter(row.labels, len = 7)
plots <- list(p1 = comp$Plots$Means, p2 = diff$Plots$Means,
p3 = diff$QQPlots$Means, p4 = comp$Plots$Variances,
p5 = diff$Plots$Variances, p6 = diff$QQPlots$Variances,
p7 = comp$Plots$MeanVar, p8 = diff$Plots$MeanVar,
p9 = comp$Plots$LibrarySizes, p10 = diff$Plots$LibrarySizes,
p11 = diff$QQPlots$LibrarySizes, p12 = comp$Plots$ZerosCell,
p13 = diff$Plots$ZerosCell, p14 = diff$QQPlots$ZerosCell,
p15 = comp$Plots$ZerosGene, p16 = diff$Plots$ZerosGene,
p17 = diff$QQPlots$ZerosGene, p18 = comp$Plots$MeanZeros,
p19 = diff$Plots$MeanZeros)
# Remove titles and legends
for (plot in names(plots)) {
plots[[plot]] <- plots[[plot]] + theme(legend.position = "none",
plot.title = element_blank())
}
# Remove x-axis title from some plots
for (plot in paste0("p", c(1, 2, 4, 5, 9, 10, 12, 13, 15, 16))) {
plots[[plot]] <- plots[[plot]] + theme(axis.title.x = element_blank())
}
plots$leg <- cowplot::get_legend(plots$p1 +
theme(legend.position = "bottom"))
panel <- cowplot::ggdraw() +
cowplot::draw_label(title, 0.5, 0.995,
fontface = "bold", size = 18) +
cowplot::draw_label(row.labels[1], 0.01, 0.985,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p1, 0.00, 0.86, 0.32, 0.12) +
cowplot::draw_plot(plots$p2, 0.34, 0.86, 0.32, 0.12) +
cowplot::draw_plot(plots$p3, 0.67, 0.86, 0.32, 0.12) +
cowplot::draw_label(row.labels[2], 0.01, 0.845,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p4, 0.00, 0.72, 0.32, 0.12) +
cowplot::draw_plot(plots$p5, 0.34, 0.72, 0.32, 0.12) +
cowplot::draw_plot(plots$p6, 0.67, 0.72, 0.32, 0.12) +
cowplot::draw_label(row.labels[3], 0.01, 0.705,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p7, 0.00, 0.58, 0.49, 0.12) +
cowplot::draw_plot(plots$p8, 0.51, 0.58, 0.49, 0.12) +
cowplot::draw_label(row.labels[4], 0.01, 0.56,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p9, 0.00, 0.44, 0.32, 0.12) +
cowplot::draw_plot(plots$p10, 0.34, 0.44, 0.32, 0.12) +
cowplot::draw_plot(plots$p11, 0.67, 0.44, 0.32, 0.12) +
cowplot::draw_label(row.labels[5], 0.01, 0.425,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p12, 0.00, 0.30, 0.32, 0.12) +
cowplot::draw_plot(plots$p13, 0.34, 0.30, 0.32, 0.12) +
cowplot::draw_plot(plots$p14, 0.67, 0.30, 0.32, 0.12) +
cowplot::draw_label(row.labels[6], 0.01, 0.285,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p15, 0.00, 0.16, 0.32, 0.12) +
cowplot::draw_plot(plots$p16, 0.34, 0.16, 0.32, 0.12) +
cowplot::draw_plot(plots$p17, 0.67, 0.16, 0.32, 0.12) +
cowplot::draw_label(row.labels[7], 0.01, 0.145,
fontface = "bold", hjust = 0, vjust = 0) +
cowplot::draw_plot(plots$p18, 0.00, 0.02, 0.49, 0.12) +
cowplot::draw_plot(plots$p19, 0.51, 0.02, 0.49, 0.12) +
cowplot::draw_plot(plots$leg, 0.00, 0.00, 1.00, 0.02)
return(panel)
}
man/compareSCESets.Rd
+ 10
− 1
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...@@ -4,10 +4,19 @@ ...@@ -4,10 +4,19 @@
\alias{compareSCESets} \alias{compareSCESets}
\title{Compare SCESet objects} \title{Compare SCESet objects}
\usage{ \usage{
compareSCESets(sces) compareSCESets(sces, point.size = 0.1, point.alpha = 0.1, fits = TRUE,
colours = NULL)
} }
\arguments{ \arguments{
\item{sces}{named list of SCESet objects to combine and compare.} \item{sces}{named list of SCESet objects to combine and compare.}
\item{point.size}{size of points in scatter plots.}
\item{point.alpha}{opacity of points in scatter plots.}
\item{fits}{whether to include fits in scatter plots.}
\item{colours}{vector of colours to use for each dataset.}
} }
\value{ \value{
List containing the combined datasets and plots. List containing the combined datasets and plots.
......
man/diffSCESets.Rd
+ 10
− 1
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...@@ -4,12 +4,21 @@ ...@@ -4,12 +4,21 @@
\alias{diffSCESets} \alias{diffSCESets}
\title{Diff SCESet objects} \title{Diff SCESet objects}
\usage{ \usage{
diffSCESets(sces, ref) diffSCESets(sces, ref, point.size = 0.1, point.alpha = 0.1, fits = TRUE,
colours = NULL)
} }
\arguments{ \arguments{
\item{sces}{named list of SCESet objects to combine and compare.} \item{sces}{named list of SCESet objects to combine and compare.}
\item{ref}{string giving the name of the SCESet to use as the reference} \item{ref}{string giving the name of the SCESet to use as the reference}
\item{point.size}{size of points in scatter plots.}
\item{point.alpha}{opacity of points in scatter plots.}
\item{fits}{whether to include fits in scatter plots.}
\item{colours}{vector of colours to use for each dataset.}
} }
\value{ \value{
List containing the combined datasets and plots. List containing the combined datasets and plots.
......
man/makeCompPanel.Rd 0 → 100644
+ 32
− 0
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/compare.R
\name{makeCompPanel}
\alias{makeCompPanel}
\title{Make comparison panel}
\usage{
makeCompPanel(comp, title = "Comparison", labels = c("Means", "Variance",
"Mean-variance relationship", "Library size", "Zeros per gene",
"Zeros per cell", "Mean-zeros relationship"))
}
\arguments{
\item{comp}{list returned by \code{\link{compareSCESets}}.}
\item{title}{title for the panel.}
\item{labels}{vector of labels for each of the seven plots.}
}
\value{
Combined panel plot
}
\description{
Combine the plots from \code{compareSCESets} into a single panel.
}
\examples{
\dontrun{
sim1 <- splatSimulate(nGenes = 1000, groupCells = 20)
sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
comparison <- compareSCESets(list(Splat = sim1, Simple = sim2))
panel <- makeCompPanel(comparison)
}
}
man/makeDiffPanel.Rd 0 → 100644
+ 32
− 0
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/compare.R
\name{makeDiffPanel}
\alias{makeDiffPanel}
\title{Make difference panel}
\usage{
makeDiffPanel(diff, title = "Difference comparison", labels = c("Means",
"Variance", "Library size", "Zeros per cell", "Zeros per gene",
"Mean-variance relationship", "Mean-zeros relationship"))
}
\arguments{
\item{diff}{list returned by \code{\link{diffSCESets}}.}
\item{title}{title for the panel.}
\item{labels}{vector of labels for each of the seven sections.}
}
\value{
Combined panel plot
}
\description{
Combine the plots from \code{diffSCESets} into a single panel.
}
\examples{
\dontrun{
sim1 <- splatSimulate(nGenes = 1000, groupCells = 20)
sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
difference <- diffSCESets(list(Splat = sim1, Simple = sim2), ref = "Simple")
panel <- makeDiffPanel(difference)
}
}
man/makeOverallPanel.Rd 0 → 100644
+ 37
− 0
View file @ c554dc43
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/compare.R
\name{makeOverallPanel}
\alias{makeOverallPanel}
\title{Make overall panel}
\usage{
makeOverallPanel(comp, diff, title = "Overall comparison",
row.labels = c("Means", "Variance", "Mean-variance relationship",
"Library size", "Zeros per cell", "Zeros per gene",
"Mean-zeros relationship"))
}
\arguments{
\item{comp}{list returned by \code{\link{compareSCESets}}.}
\item{diff}{list returned by \code{\link{diffSCESets}}.}
\item{title}{title for the panel.}
\item{row.labels}{vector of labels for each of the seven rows.}
}
\value{
Combined panel plot
}
\description{
Combine the plots from \code{compSCESets} and \code{diffSCESets} into a
single panel.
}
\examples{
\dontrun{
sim1 <- splatSimulate(nGenes = 1000, groupCells = 20)
sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
comparison <- compSCESets(list(Splat = sim1, Simple = sim2))
difference <- diffSCESets(list(Splat = sim1, Simple = sim2), ref = "Simple")
panel <- makeOverallPanel(comparison, difference)
}
}
vignettes/splatter.Rmd
+ 24
− 0
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...@@ -473,6 +473,30 @@ distributions. ...@@ -473,6 +473,30 @@ distributions.
difference$QQPlots$Means difference$QQPlots$Means
``` ```
## Making panels
Each of these comparisons makes several plots which can be a lot to look at. To
make this easier, or to produce figures for publications, you can make use of
the functions `makeCompPanel`, `makeDiffPanel` and `makeOverallPanel`.
These functions combine the plots into a single panel using the `cowplot`
package. The panels can be quite large and hard to view (for example in
RStudio's plot viewer) so it can be better to output the panels and view them
separately. Luckily `cowplot` provides a convenient function for saving the
images. Here are some suggested parameters for outputting each of the panels:
```{r save-panels, eval = FALSE}
# This code is just an example and is not run
panel <- makeCompPanel(comparison)
cowplot::save_plot("comp_panel.png", panel, nrow = 4, ncol = 3)
panel <- makeDiffPanel(difference)
cowplot::save_plot("diff_panel.png", panel, nrow = 3, ncol = 5)
panel <- makeOverallPanel(comparison, difference)
cowplot::save_plot("overall_panel.png", panel, ncol = 4, nrow = 7)
```
# Session information {-} # Session information {-}
```{r sessionInfo} ```{r sessionInfo}
......
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