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add fig S6
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@wikiselev
wikiselev committed Feb 28, 2017
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8 changes: 8 additions & 0 deletions README.md
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Expand Up @@ -67,6 +67,14 @@ This repository contains scripts for recreation of the figures from the SC3 pape

![](jpeg/S5b.jpeg)

### Fig. S6
[data_b](data/S6b.csv)
[data_c](data/S6c.csv)
[script](S6.R)
[pdf](pdf/S6.pdf)

![](jpeg/S5a.jpeg)

## Session Info

```
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5 changes: 3 additions & 2 deletions S4.R
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Expand Up @@ -133,15 +133,16 @@ get_c <- function() {
theme_classic(base_size = font_size) +
theme(axis.ticks.x = element_blank(), axis.text.x=element_blank(),
axis.title.x=element_blank(), axis.line=element_blank(),
strip.background = element_rect(colour = "white")) +
strip.background = element_rect(colour = "white"),
legend.key.size = unit(0.4, "cm")) +
ylim(0,1) +
annotate("segment", x=-Inf, xend=Inf, y=-Inf, yend=-Inf, color = "black")+
annotate("segment", x=-Inf, xend=-Inf, y=-Inf, yend=Inf, color = "black")
p <- ggdraw(p) +
draw_label("% of total # of cells\nin a training set",
fontface = "bold",
size = font_size-3,
x = 0.86, y = 0.93)
x = 0.87, y = 0.93)
return(p)
}

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90 changes: 90 additions & 0 deletions S6.R
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@@ -0,0 +1,90 @@
library(cowplot)
library(dplyr)
library(pheatmap)

options(stringsAsFactors = FALSE)
font_size <- 7

get_a <- function() {
de.genes = rbind(
c(1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
c(0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0),
c(0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0),
c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1),
c(1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0),
c(1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0),
c(1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1),
c(0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0),
c(0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1),
c(0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1),
c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0),
c(1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1),
c(1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1),
c(0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1)
)

colnames(de.genes) = paste("Cell ", 1:20, sep = "")
rownames(de.genes) = paste("Gene ", 1:14, sep = "")

p <- pheatmap(de.genes,
cluster_row = FALSE,
cluster_cols = FALSE,
gaps_col = c(5, 10, 15),
gaps_row = 4,
legend = F,
fontsize = font_size,
silent = TRUE)
return(p$gtable)
}

get_b <- function() {
cols <- c("Biase" = "#bc80bd", "Treutlein" = "#8dd3c7", "Ting" = "#ffffb3",
"Yan" = "#ccebc5", "Goolam" = "#ffed6f", "Deng" = "#bebada",
"Pollen1" = "#fb8072", "Pollen1-TopHat" = "#fb8072",
"Pollen2-TopHat" = "#fb8072", "Pollen2" = "#fb8072",
"Patel" = "#80b1d3", "Usoskin1" = "#fdb462", "Usoskin2" = "#fdb462",
"Usoskin3" = "#fdb462", "Kolodziejczyk" = "#bf812d",
"Klein" = "#b3de69", "Zeisel" = "#fccde5", "Macosko" = "#d9d9d9")

d <- read.csv("data/S6c.csv")

d$Dataset <- factor(d$Dataset, levels = c("Biase", "Yan", "Goolam", "Deng",
"Pollen1", "Pollen2", "Kolodziejczyk",
"Treutlein", "Ting", "Patel",
"Usoskin1", "Usoskin2", "Usoskin3",
"Klein", "Zeisel", "Macosko"))

p <- ggplot(d, aes(x = AUROC, colour = Dataset, fill = Dataset)) +
geom_density(alpha = 0.6) +
scale_fill_manual(values = cols) +
scale_colour_manual(values = cols) +
labs(y = "Density") +
theme_classic(base_size = font_size) +
theme(legend.key.size = unit(0.4, "cm"))

return(p)
}

get_c <- function() {
d <- read.csv("data/S6b.csv")
d$Stage <- factor(d$Stage, levels = unique(d$Stage))
cols <- c("#A6CEE3", "#1F78B4", "#B2DF8A", "#33A02C", "#FB9A99",
"#FF00FF", "#FDBF6F", "#FF7F00", "#CAB2D6", "#6A3D9A")
p <- ggplot(d, aes(x = Cells, y = outl, fill = Stage, color = Stage)) +
geom_bar(stat = "identity") +
scale_fill_manual(values = cols) +
scale_color_manual(values = cols) +
labs(y = "Outlier score") +
theme_classic(base_size = font_size) +
theme(legend.key.size = unit(0.4, "cm"))
return(p)
}

first_row <- plot_grid(NULL, get_a(), NULL, get_b(), ncol = 4, labels = c("a", "", "", "b"), rel_widths = c(0.2,0.6,0.2,1))
second_row <- plot_grid(get_c(), ncol = 1, labels = c("c"))

plot_grid(first_row, second_row, nrow = 2, rel_heights = c(1.5, 1))

ggsave("jpeg/S6.jpeg", w = 9, h = 6)
ggsave("pdf/S6.pdf", w = 9, h = 6)

269 changes: 269 additions & 0 deletions data/S6b.csv
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