3abc.Rmd

---
title: "Figure 3"
output:
  html_document:
    df_print: paged
---


```{r message=FALSE, warning=FALSE}
suppressPackageStartupMessages(source("scripts/themes.R"))
tm.facs <- loadObject(filename = url("https://scfind.cog.sanger.ac.uk/indexes/tm_facs.rds"))
```

## Figure 3a
```{r message=FALSE, warning=FALSE, paged.print=TRUE}
result <- markerGenes(tm.facs, 
            gene.list = c("Acta1", "Actc1", "Atp2a2", "Myh6", "Nppa", "Ryr2", "Tnnc1", "Tpm"))

table.4a <- hyperQueryCellTypes(tm.facs, 
                    gene.list = strsplit(as.character(result$Query[which.max(result$tfidf)]), ",")[[1]])

head(result[order(result$tfidf, decreasing = T),])
table.4a[order(table.4a$pval, decreasing = F),]
```


## Figure 3b
```{r eval=FALSE, message=FALSE, warning=FALSE}
df.4b <- readRDS("data/fig4b.rds")

ha = rowAnnotation("Tissue" = df.4b$tissues,
                   col = list("Tissue" = df.4b$colour18),
                   cells = anno_mark(at = c(32:38, 73:77, 102:106, 109),
                                     labels = rownames(df.4b$mx)[ c(32:38, 73:77, 102:106, 109)] ),
                   annotation_legend_param = list( "Tissue" = list(nrow = 2)))

ta = HeatmapAnnotation("GO parents" = df.4b$V3,
                       col = list("GO parents" = df.4b$colourAncestors),
                       annotation_legend_param = list( "GO parents" = list(nrow = 2)))

draw(Heatmap(df.4b$mx, name = "-log10(p-value)",
        cluster_rows = F, show_row_names = F,
        cluster_columns = F,show_column_names = F,
        col = c("white", brewer.pal(9, "RdPu")), na_col = "#49006A",
        column_title = NULL,
        top_annotation = ta,
        right_annotation = ha
        ) ,
     heatmap_legend_side = "right", annotation_legend_side = "bottom"
     )
```


## Figure 3c
```{r message=FALSE, warning=FALSE}
df.4c <- read.table("data/fig4c.csv", sep = ",", header = T, stringsAsFactors = F)
df.4c$atlas <- factor(df.4c$atlas, levels = gsub("\\s", "\n", legend_order))

log_scale_y <- scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x), 
                             labels = trans_format("log10", math_format(10^.x)), 
                             limits = c(-1,100)
                             )

p.4c <- ggplot(data = df.4c, aes(x = gene_number, y = x, colour = atlas)) + 
    main  + log_scale_y +
    labs(colour = "Atlas") + xlab("Number of genes") + ylab("Mean time (sec)") + 
    scale_colour_manual(values=RColorBrewer::brewer.pal(8,colorcode)[c(1:4, 6)]) +
    geom_point(size = dotsize) + geom_line(size = linesize) + geom_ribbon(aes(ymin=df.4c$x + df.4c$se, ymax = df.4c$x - df.4c$se), linetype = 1, alpha = 0.1) + xlim(5, 25)
```


### Figure 3
```{r echo=FALSE, fig.height=5, fig.retina=10, fig.width=8, message=FALSE, warning=FALSE}
plot_grid(NULL,
          p.4c, 
          labels = c('A','C'), 
          nrow = 2, ncol =2
          )
```