library(tidyverse)
library(cowplot)
library(here)
draw_mean_variance_plot <- function(df_count, title) {
require(tidyverse)
require(matrixStats)
df_norm <- df_count
for(i in 1:ncol(df_norm)) {
df_norm[,i] <- df_count[,i] / sum(df_count[,i]) * 10^6
}
means <- rowMeans(df_norm)
vars <- rowVars(df_norm %>% as.matrix)
tibble(m = log10(means), v = log10(vars)) %>%
ggplot(aes(x=m,y=v)) +
geom_point(alpha=0.5, size = 0.5, color = "grey") +
geom_abline(slope = 1, intercept = 0, color="red") +
geom_smooth() +
ggtitle(title) + xlab(bquote(log[10]~"(meanCPM)")) + ylab(bquote(log[10]~"(varianceCPM)"))
}
p1 <- read_csv("../01_gene-level-analysis/data/Evers/CRISPRn-RT112.csv")  %>%
select(sgRNA, B1,B2, B3) %>% column_to_rownames("sgRNA") %>% draw_mean_variance_plot(title = "CRISPRn-RT112 (T0)")
p2 <- read_tsv("../01_gene-level-analysis/data/Sanson/CRISPRn-A375.tsv")  %>%
select(sgRNA, RepA, RepB, RepC) %>% column_to_rownames("sgRNA") %>% draw_mean_variance_plot(title = "CRISPRn-A375")
p3 <- read_tsv("../02_sgRNA-level-analysis/dat/Gsk3_readcount.txt")  %>%
select(gRNA, Before_1, Before_2, Before_3, Before_4) %>% column_to_rownames("gRNA") %>% draw_mean_variance_plot(title = "Gsk3 (Before)")
plot_grid(p1, p2, p3, nrow = 1, labels = "AUTO")
save_plot("figures/fig-S1.png", last_plot(), base_height = 3, base_width = 8)
library(tidyverse)
library(cowplot)
library(here)
draw_mean_variance_plot <- function(df_count, title) {
require(tidyverse)
require(matrixStats)
df_norm <- df_count
for(i in 1:ncol(df_norm)) {
df_norm[,i] <- df_count[,i] / sum(df_count[,i]) * 10^6
}
means <- rowMeans(df_norm)
vars <- rowVars(df_norm %>% as.matrix)
tibble(m = log10(means), v = log10(vars)) %>%
ggplot(aes(x=m,y=v)) +
geom_point(alpha=0.5, size = 0.5) +
geom_abline(slope = 1, intercept = 0, color="red") +
geom_smooth(method = "GAM", se = FALSE) +
ggtitle(title) + xlab(bquote(log[10]~"(meanCPM)")) + ylab(bquote(log[10]~"(varianceCPM)"))
}
p1 <- read_csv("../01_gene-level-analysis/data/Evers/CRISPRn-RT112.csv")  %>%
select(sgRNA, B1,B2, B3) %>% column_to_rownames("sgRNA") %>% draw_mean_variance_plot(title = "CRISPRn-RT112 (T0)")
p2 <- read_tsv("../01_gene-level-analysis/data/Sanson/CRISPRn-A375.tsv")  %>%
select(sgRNA, RepA, RepB, RepC) %>% column_to_rownames("sgRNA") %>% draw_mean_variance_plot(title = "CRISPRn-A375")
p3 <- read_tsv("../02_sgRNA-level-analysis/dat/Gsk3_readcount.txt")  %>%
select(gRNA, Before_1, Before_2, Before_3, Before_4) %>% column_to_rownames("gRNA") %>% draw_mean_variance_plot(title = "Gsk3 (Before)")
plot_grid(p1, p2, p3, nrow = 1, labels = "AUTO")
save_plot("figures/fig-S1.png", last_plot(), base_height = 3, base_width = 8)
?geom_smooth
source('~/Projects/CB2-Experiments/02_sgRNA-level-analysis/draw-fig-S1.R')
