From 8e396958501437450b67cb6bd8adb69c875feaa9 Mon Sep 17 00:00:00 2001
From: Luke Zappia <lazappi@users.noreply.github.com>
Date: Wed, 21 Aug 2019 17:30:57 +1000
Subject: [PATCH] Add violins to comparison plots
---
NEWS.md | 1 +
R/compare.R | 56 ++++++++++++++++++++++++++++++++++++-----------------
2 files changed, 39 insertions(+), 18 deletions(-)
diff --git a/NEWS.md b/NEWS.md
index 2aa1416..8ccfac0 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,7 @@
### Version 1.9.4.9009 (2019-08-21)
* Replace library size log-normal with density and rejection sampling
+* Add violins to comparison plots
### Version 1.9.4.9008 (2019-08-20)
diff --git a/R/compare.R b/R/compare.R
index dba07d3..e1f4100 100644
--- a/R/compare.R
+++ b/R/compare.R
@@ -52,9 +52,9 @@
#' names(comparison)
#' names(comparison$Plots)
#' @importFrom ggplot2 ggplot aes_string geom_point geom_smooth geom_boxplot
-#' geom_tile scale_y_continuous scale_y_log10 scale_x_log10 scale_colour_manual
-#' scale_fill_manual scale_fill_distiller coord_fixed facet_wrap xlab ylab
-#' ggtitle theme_minimal
+#' geom_violin geom_tile scale_y_continuous scale_y_log10 scale_x_log10
+#' scale_colour_manual scale_fill_manual scale_fill_distiller coord_fixed
+#' facet_wrap xlab ylab ggtitle theme_minimal
#' @importFrom S4Vectors metadata<- metadata
#' @importFrom SingleCellExperiment cpm<- cpm
#' @importFrom stats cor
@@ -125,8 +125,12 @@ compareSCEs <- function(sces, point.size = 0.1, point.alpha = 0.1,
means <- ggplot(features,
aes_string(x = "Dataset", y = "MeanLogCPM",
colour = "Dataset")) +
- geom_boxplot() +
+ geom_violin(aes_string(fill = "Dataset"),
+ draw_quantiles = c(0.25, 0.5, 0.75),
+ colour = "white", alpha = 0.3, size = 0.8) +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
+ scale_fill_manual(values = colours) +
ylab(expression(paste("Mean ", log[2], "(CPM + 1)"))) +
ggtitle("Distribution of mean expression") +
theme_minimal()
@@ -134,8 +138,12 @@ compareSCEs <- function(sces, point.size = 0.1, point.alpha = 0.1,
vars <- ggplot(features,
aes_string(x = "Dataset", y = "VarLogCPM",
colour = "Dataset")) +
- geom_boxplot() +
+ geom_violin(aes_string(fill = "Dataset"),
+ draw_quantiles = c(0.25, 0.5, 0.75),
+ colour = "white", alpha = 0.3, size = 0.8) +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
+ scale_fill_manual(values = colours) +
ylab(expression(paste("Variance ", log[2], "(CPM + 1)"))) +
ggtitle("Distribution of variance") +
theme_minimal()
@@ -154,9 +162,13 @@ compareSCEs <- function(sces, point.size = 0.1, point.alpha = 0.1,
libs <- ggplot(cells,
aes_string(x = "Dataset", y = "sum",
colour = "Dataset")) +
- geom_boxplot() +
+ geom_violin(aes_string(fill = "Dataset"),
+ draw_quantiles = c(0.25, 0.5, 0.75),
+ colour = "white", alpha = 0.3, size = 0.8) +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_y_continuous(labels = scales::comma) +
scale_colour_manual(values = colours) +
+ scale_fill_manual(values = colours) +
ylab("Total counts per cell") +
ggtitle("Distribution of library sizes") +
theme_minimal()
@@ -164,9 +176,13 @@ compareSCEs <- function(sces, point.size = 0.1, point.alpha = 0.1,
z.gene <- ggplot(features,
aes_string(x = "Dataset", y = "PctZero",
colour = "Dataset")) +
- geom_boxplot() +
+ geom_violin(aes_string(fill = "Dataset"),
+ draw_quantiles = c(0.25, 0.5, 0.75),
+ colour = "white", alpha = 0.3, size = 0.8) +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_y_continuous(limits = c(0, 100)) +
scale_colour_manual(values = colours) +
+ scale_fill_manual(values = colours) +
ylab("Percentage zeros per gene") +
ggtitle("Distribution of zeros per gene") +
theme_minimal()
@@ -174,9 +190,13 @@ compareSCEs <- function(sces, point.size = 0.1, point.alpha = 0.1,
z.cell <- ggplot(cells,
aes_string(x = "Dataset", y = "PctZero",
colour = "Dataset")) +
- geom_boxplot() +
+ geom_violin(aes_string(fill = "Dataset"),
+ draw_quantiles = c(0.25, 0.5, 0.75),
+ colour = "white", alpha = 0.3, size = 0.8) +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_y_continuous(limits = c(0, 100)) +
scale_colour_manual(values = colours) +
+ scale_fill_manual(values = colours) +
ylab("Percentage zeros per cell") +
ggtitle("Distribution of zeros per cell") +
theme_minimal()
@@ -413,7 +433,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "Dataset", y = "RankDiffMeanLogCPM",
colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") +
- geom_boxplot() +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
ylab(expression(paste("Rank difference mean ", log[2], "(CPM + 1)"))) +
ggtitle("Difference in mean expression") +
@@ -423,7 +443,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "Dataset", y = "RankDiffVarLogCPM",
colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") +
- geom_boxplot() +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
ylab(expression(paste("Rank difference variance ", log[2],
"(CPM + 1)"))) +
@@ -447,7 +467,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "Dataset", y = "RankDiffLibSize",
colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") +
- geom_boxplot() +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
ylab(paste("Rank difference library size")) +
ggtitle("Difference in library sizes") +
@@ -457,7 +477,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "Dataset", y = "RankDiffZeros",
colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") +
- geom_boxplot() +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
ylab(paste("Rank difference percentage zeros")) +
ggtitle("Difference in zeros per gene") +
@@ -467,7 +487,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "Dataset", y = "RankDiffZeros",
colour = "Dataset")) +
geom_hline(yintercept = 0, colour = "red") +
- geom_boxplot() +
+ geom_boxplot(notch = TRUE, width = 0.1, size = 0.8) +
scale_colour_manual(values = colours) +
ylab(paste("Rank difference percentage zeros")) +
ggtitle("Difference in zeros per cell") +
@@ -489,7 +509,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "RefRankMeanLogCPM", y = "MeanLogCPM",
colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") +
- geom_point(size = point.size, alpha = point.alpha) +
+ geom_point(size = point.size) +
scale_colour_manual(values = colours) +
xlab(expression(paste("Reference mean ", log[2], "(CPM + 1)"))) +
ylab(expression(paste("Alternative mean ", log[2], "(CPM + 1)"))) +
@@ -500,7 +520,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "RefRankVarLogCPM", y = "VarLogCPM",
colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") +
- geom_point(size = point.size, alpha = point.alpha) +
+ geom_point(size = point.size) +
scale_colour_manual(values = colours) +
xlab(expression(paste("Reference variance ", log[2], "(CPM + 1)"))) +
ylab(expression(paste("Alternative variance ", log[2], "(CPM + 1)"))) +
@@ -511,7 +531,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "RefRankLibSize", y = "sum",
colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") +
- geom_point(size = point.size, alpha = point.alpha) +
+ geom_point(size = point.size) +
scale_colour_manual(values = colours) +
xlab("Reference library size") +
ylab("Alternative library size") +
@@ -523,7 +543,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
y = "PctZero",
colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") +
- geom_point(size = point.size, alpha = point.alpha) +
+ geom_point(size = point.size) +
scale_colour_manual(values = colours) +
xlab("Reference percentage zeros") +
ylab("Alternative percentage zeros") +
@@ -534,7 +554,7 @@ diffSCEs <- function(sces, ref, point.size = 0.1, point.alpha = 0.1,
aes_string(x = "RefRankZeros", y = "PctZero",
colour = "Dataset")) +
geom_abline(intercept = 0, slope = 1, colour = "red") +
- geom_point(size = point.size, alpha = point.alpha) +
+ geom_point(size = point.size) +
scale_colour_manual(values = colours) +
xlab("Reference percentage zeros") +
ylab("Alternative percentage zeros") +
--
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