add all other figures

2.R

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+library(cowplot)
+library(pheatmap)
+library(dplyr)
+
+set.seed(12323414)
+options(stringsAsFactors = FALSE)
+font_size <- 8
+
+gtable_select <- function (x, ...)
+{
+    matches <- c(...)
+    x$layout <- x$layout[matches, , drop = FALSE]
+    x$grobs <- x$grobs[matches]
+    x
+}
+
+gtable_stack <- function(g1, g2){
+    g1$grobs <- c(g1$grobs, g2$grobs)
+    g1$layout <- transform(g1$layout, z= z-max(z), name="g2")
+    g1$layout <- rbind(g1$layout, g2$layout)
+    g1
+}
+
+get_a <- function() {
+    d <- read.csv("data/2a.csv")
+
+    d[d$Hierarchy == "Kolodziejczyk", ]$Hierarchy <- "Kolodz."
+
+    d$Hierarchy <- factor(
+        d$Hierarchy, 
+        levels = c("Biase", "Yan", "Goolam", "Deng", "Pollen1", "Pollen2", 
+                   "Kolodz.", "Treutlein", "Ting",
+                    "Patel", "Usoskin1", "Usoskin2", "Usoskin3",
+                    "Klein", "Zeisel")
+    )
+
+    d$Method <- factor(
+        d$Method, 
+        levels = c("SC3", "tSNE+kmeans", "pcaReduce", "SNN-Cliq", "SINCERA", "SEURAT")
+    )
+
+    cols <- c("Biase" = "#bc80bd", "Treutlein" = "#8dd3c7", "Ting" = "#ffffb3", 
+              "Yan" = "#ccebc5", "Goolam" = "#ffed6f", "Deng" = "#bebada",
+              "Pollen1" = "#fb8072", "Pollen2" = "#fb8072",
+              "Patel" = "#80b1d3", "Usoskin1" = "#fdb462", "Usoskin2" = "#fdb462",
+              "Usoskin3" = "#fdb462", "Kolodz." = "#bf812d",
+              "Klein" = "#b3de69", "Zeisel" = "#fccde5", "Macosko" = "#d9d9d9")
+
+    meth_cols <- c(
+        "SC3" = "#e41a1c", 
+        "tSNE+kmeans" = "#377eb8", 
+        "pcaReduce" = "#40E0D0", 
+        "SNN-Cliq" = "#984ea3", 
+        "SINCERA" = "#ff7f00", 
+        "SEURAT" = "#ffff33"
+    )
+
+    d1 <- d %>%
+        group_by(Method, Hierarchy) %>%
+        dplyr::summarise(Median = median(ARI))
+
+    p <- ggplot(d, aes(x = 1, y = ARI, fill = Method, group = Method)) +
+        geom_bar(data = d1, aes(y = Median), position="dodge", stat="identity") +
+        geom_point(position = position_jitterdodge(jitter.width = 0.45, dodge.width = 0.9), size = 0.4) +
+        facet_wrap(ncol = 5, ~ Hierarchy) +
+        scale_fill_manual(values = meth_cols) +
+        scale_colour_manual(values = meth_cols) +
+        geom_hline(yintercept = 0.8) +
+        labs(x = "") +
+        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(),
+              legend.key.size = unit(0.4, "cm")) +
+        annotate("segment", x=-Inf, xend=Inf, y=-Inf, yend=-Inf, color = "black")+
+        annotate("segment", x=-Inf, xend=-Inf, y=-Inf, yend=Inf, color = "black")
+
+
+    dummy <- ggplot(d, aes(x = 1, y = ARI, fill = Method)) +
+        facet_wrap(ncol = 5, ~ Hierarchy) +
+        geom_rect(aes(fill = Hierarchy), xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) +
+        scale_fill_manual(values = cols) +
+        theme_minimal()
+
+    g1 <- ggplotGrob(p)
+    g2 <- ggplotGrob(dummy)
+
+    panels <- grepl(pattern="panel", g2$layout$name)
+    strips <- grepl(pattern="strip-t", g2$layout$name)
+    g2$layout$t[panels] <- g2$layout$t[panels] - 1
+    g2$layout$b[panels] <- g2$layout$b[panels] - 1
+
+    new_strips <- gtable_select(g2, panels | strips)
+
+    new_plot <- gtable_stack(g1, new_strips)
+    return(new_plot)
+}
+
+get_c <- function() {
+    cols <- c("Treutlein" = "#8dd3c7", "Ting" = "#ffffb3", "Deng" = "#bebada",
+              "Pollen2" = "#fb8072", "Patel" = "#80b1d3", 
+              "Kolodziejczyk" = "#bf812d", "Usoskin3" = "#fdb462",
+              "Klein" = "#40E0D0", "Zeisel" = "#fccde5", "Macosko" = "#d9d9d9")
+
+    d <- read.csv("data/2c.csv")
+
+    d$Dataset <- factor(
+        d$Dataset,
+        levels = c(
+            "Deng",
+            "Pollen2",
+            "Kolodziejczyk",
+            "Patel",
+            "Usoskin3",
+            "Klein",
+            "Zeisel",
+            "Macosko"
+        )
+    )
+
+    d$Fraction <- factor(
+        d$Fraction,
+        levels = sort(unique(as.numeric(d$Fraction)))
+    )
+
+    p <- ggplot(d, aes(x = 1, ARI, fill = Dataset, color = Dataset)) +
+        geom_boxplot(position = position_dodge(width = 1.5), outlier.size = 0.8) +
+        geom_hline(yintercept = 0.8) +
+        labs(x = "# of training cells as % of N", y = "ARI") +
+        scale_fill_manual(values = cols) +
+        scale_colour_manual(values = cols) +
+        facet_grid(. ~ Fraction) +
+        theme_classic(base_size = font_size) +
+        theme(axis.ticks.x = element_blank(), axis.text.x=element_blank(),
+              axis.title.x=element_blank(), axis.line=element_blank(),
+              strip.background = element_rect(colour = "white"),
+              legend.key.size = unit(0.4, "cm")) +
+        ylim(0,1) +
+        annotate("segment", x=-Inf, xend=Inf, y=-Inf, yend=-Inf, color = "black")+
+        annotate("segment", x=-Inf, xend=-Inf, y=-Inf, yend=Inf, color = "black")
+    p <- ggdraw(p) + 
+        draw_label("% of total # of cells\nin a training set", 
+                   fontface = "bold",
+                   size = font_size-3,
+                   x = 0.87, y = 0.93)
+    return(p)
+}
+
+get_d <- function() {
+    d <- readRDS("data/2d.rds")
+    ann <- data.frame(Stage = factor(d$cell.names, levels = unique(d$cell.names)))
+    anno_colors <- list(Stage = c("#A6CEE3", "#1F78B4", "#B2DF8A", "#33A02C",
+                                  "#FB9A99", "#FF00FF", "#FDBF6F", "#FF7F00", 
+                                  "#CAB2D6", "#6A3D9A"))
+    names(anno_colors$Stage) <- levels(ann$Stage)
+    dat <- d$consensus
+    colnames(dat) <- d$cell.names
+    write.csv(dat[d$hc$order, d$hc$order], file = "data/2d.csv", quote = FALSE, row.names = FALSE)
+    p <- pheatmap(d$consensus,
+             cluster_rows = d$hc,
+             cluster_cols = d$hc,
+             cutree_rows = 10,
+             cutree_cols = 10,
+             treeheight_col = 9,
+             treeheight_row = 9,
+             annotation_col = ann,
+             annotation_colors = anno_colors,
+             show_rownames = F,
+             show_colnames = F,
+             fontsize = font_size,
+             annotation_names_col = F,
+             silent = TRUE)
+    return(p$gtable)
+}
+
+first_col <- plot_grid(get_a(), get_c(), nrow = 2, labels = c("a", "c"), rel_heights = c(2, 1))
+
+second_col <- plot_grid(NULL, get_d(), nrow = 2, labels = c("b", "d"), rel_heights = c(1.5, 1))
+
+plot_grid(first_col, second_col, ncol = 2)
+
+ggsave("jpeg/2.jpeg", w = 9, h = 6)
+ggsave("pdf/2.pdf", w = 9, h = 6)
+

3.R

@@ -0,0 +1,28 @@
+library(pheatmap)
+library(cowplot)
+
+options(stringsAsFactors = FALSE)
+font_size <- 8
+
+d <- readRDS("data/3.rds")
+
+dat <- d$exprs
+write.csv(dat[, d$hc$order], file = "data/3.csv", quote = FALSE, row.names = FALSE)
+
+anno_colors <- list(Cluster = c("#e41a1c", "#984ea3", "#40E0D0", "#FFFF33"))
+names(anno_colors$Cluster) <- levels(d$ann$Cluster)
+
+p <- pheatmap(d$exprs,
+         cluster_cols = d$hc,
+         cluster_rows = F,
+         cutree_cols = 3,
+         gaps_row = c(10, 20),
+         annotation_col = d$ann,
+         annotation_colors = anno_colors,
+         show_colnames = F,
+         silent = T)
+
+plot_grid(p$gtable, nrow = 1)
+
+ggsave("jpeg/3.jpeg", w = 9, h = 6)
+ggsave("pdf/3.pdf", w = 9, h = 6)

README.md

@@ -21,6 +21,22 @@ This repository contains scripts for recreation of the figures from the SC3 pape
 
 ![](jpeg/1d.jpeg)
 
+### Fig. 2
+[data_a](data/2a.csv)  
+[data_c](data/2c.csv)  
+[data_d](data/2d.csv)  
+[script](2.R)  
+[pdf](pdf/2.pdf)
+
+![](jpeg/2.jpeg)
+
+### Fig. 3
+[data](data/3.csv)  
+[script](3.R)  
+[pdf](pdf/3.pdf)
+
+![](jpeg/3.jpeg)
+
 ### Fig. S1
 
 [data](data/S1.csv)  
@@ -76,6 +92,22 @@ This repository contains scripts for recreation of the figures from the SC3 pape
 
 ![](jpeg/S6.jpeg)
 
+### Fig. S7
+[data_a1](data/S7a1.csv)  
+[data_a2](data/S7a2.csv)  
+[data_b1](data/S7b1.csv)  
+[data_b2](data/S7b2.csv)  
+[script](S7.R)  
+
+![](jpeg/S7.jpeg)
+
+### Fig. S12
+[data_a](data/S12a.csv)  
+[script](S12.R)  
+[pdf](pdf/S12.pdf)
+
+![](jpeg/S12.jpeg)
+
 ## Session Info
 
 ```

S12.R

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+library(cowplot)
+
+d <- read.csv("data/S12a.csv")
+
+d$Genotype <- factor(d$Genotype, levels = c("WT", "Tet2"))
+
+p <- ggplot(d, aes(Genotype, CoV)) +
+    geom_boxplot(width = 0.3) +
+    theme_classic(base_size = 9) +
+    labs(x = "", y = "Coefficient of variation")
+
+plot_grid(p, NULL, ncol = 2, labels = c("a", "b"))
+
+ggsave("pdf/S12.pdf", w = 9, h = 6)
+ggsave("jpeg/S12.jpeg", w = 9, h = 6)

S7.R

@@ -0,0 +1,38 @@
+library(cowplot)
+
+options(stringsAsFactors = FALSE)
+font_size <- 9
+
+d1 <- read.csv("data/S7a1.csv")
+d2 <- read.csv("data/S7a2.csv")
+ercc.fraction1 <- read.csv("data/S7b1.csv")
+ercc.fraction2 <- read.csv("data/S7b2.csv")
+
+p1 <- ggplot(d1, aes(x)) +
+    geom_histogram(bins = 130) + 
+    geom_vline(xintercept = 420, color = "red") +
+    labs(x = "# of expressed genes", y = "# of cells", title = "Patient 1") +
+    theme_classic(base_size = font_size)
+
+p2 <- ggplot(d2, aes(x)) +
+    geom_histogram(bins = 130) + 
+    geom_vline(xintercept = 900, color = "red") +
+    labs(x = "# of expressed genes", y = "# of cells", title = "Patient 2") +
+    theme_classic(base_size = font_size)
+
+p3 <- ggplot(ercc.fraction1, aes(x)) +
+    geom_histogram(bins = 100) + 
+    labs(x = "(# of ERCC reads)/(# endogenous reads)", y = "# of cells") +
+    xlim(0, 0.15) +
+    theme_classic(base_size = font_size)
+
+p4 <- ggplot(ercc.fraction2, aes(x)) +
+    geom_histogram(bins = 100) + 
+    labs(x = "(# of ERCC reads)/(# endogenous reads)", y = "# of cells") +
+    xlim(0, 0.15) +
+    geom_vline(xintercept = 0.05, color = "red") +
+    theme_classic(base_size = font_size)
+
+plot_grid(p1, p2, p3, p4, ncol = 2, labels = c("a", "", "b", ""))
+
+ggsave("jpeg/S8.jpeg", w = 9, h = 6)