using ggplot2 in R (geom_rect) to visualise multiple positions along stacked bars of different lengths

Question

Imagine I have 4 samples of different sizes, and within each sample I have sequential positions from m to n.

I'd like to visualise the length of each sample with a coloured bar, and place lines indicating the positions within a sample, like this:

This is what I have so far, however I don’t want the positions to be stored in separate data frames.

library("ggplot2") 

# data for coloured bars (samples)
dat=data.frame(x1=c(1,1,1,1), x2=c(200,100,270,500), y1=c(1.1,1.3,1.5,1.7), y2=c(1.2,1.4,1.6,1.8), samp=c('1','2','3','4'))

# data for each position within each sample 
pos1=data.frame(x1=c(100,50,24,100), x2=c(101,51,25,101), y1=c(1.1,1.3,1.5,1.7), y2=c(1.2,1.4,1.6,1.8), samp=c('1','2','3','4'))
pos2=data.frame(x1=c(110,65,120,405), x2=c(111,66,121,406), y1=c(1.1,1.3,1.5,1.7), y2=c(1.2,1.4,1.6,1.8), samp=c('1','2','3','4'))
pos3=data.frame(x1=c(190,70,240,442), x2=c(191,71,241,443), y1=c(1.1,1.3,1.5,1.7), y2=c(1.2,1.4,1.6,1.8), samp=c('1','2','3','4'))

# plot each sample above the next 
ggplot() + 
  scale_x_continuous(name="x") + 
  scale_y_continuous(name="y") +
  geom_rect(data=dat, mapping=aes(xmin=x1, xmax=x2, ymin=y1, ymax=y2, fill=samp), color="black", alpha=0.5) +
  geom_text(data=dat, aes(x=x1, y=y1, label=samp), size=4) +
  geom_rect(data=pos1, mapping=aes(xmin=x1, xmax=x2, ymin=y1, ymax=y2), color="black", alpha=0.5) +
  geom_rect(data=pos2, mapping=aes(xmin=x1, xmax=x2, ymin=y1, ymax=y2), color="black", alpha=0.5) +
  geom_rect(data=pos3, mapping=aes(xmin=x1, xmax=x2, ymin=y1, ymax=y2), color="black", alpha=0.5) 

Can anyone help me to plot this with pos1, pos2, and pos3 combined into a single data frame? I'm also open to suggestions for better ways of doing this!

This is a very simplified version of the data. I have around 20 samples in total, and hundreds of positions per sample.

Any help would be much appreciated!

Cheers : )

EDIT #1:

My raw data looks something like this:

positions=data.frame(sample=c(1,1,1,2,2,2,3,3,3,4,4,4),position=c(100,110,190,50,65,70,24,120,240,100,405,442))

samples=data.frame(sample=c(1,2,3,4), length=c(200,100,270,500))

Answer 1

Update:

I looked at the data again and I think this is more in line with what you are asking for:

dat2 <- dat %>% 
  mutate(x2 = 0, obs = 0) %>% 
  bind_rows(pos1 %>% mutate(obs = 1)) %>% 
  bind_rows(pos2 %>% mutate(obs = 2)) %>% 
  bind_rows(pos3 %>% mutate(obs = 3)) %>% 
  bind_rows(dat %>% mutate(obs = 4)) %>% 
  group_by(samp) %>% 
  mutate(x = x2 - lag(x2))

ggplot(dat2, aes(x=samp)) +
  geom_col(aes(y=x, fill=obs), color="black", alpha=0.5) +
  coord_flip() +
  scale_fill_gradient(low="steelblue", high="steelblue") +
  theme(legend.position = "none")

Original Answer:

I'm not sure I'm reading your data correctly, but here is an attempt:

dat2 <- dat %>% 
  mutate(obs = 0) %>% 
  bind_rows(pos1 %>% mutate(obs = 1)) %>% 
  bind_rows(pos2 %>% mutate(obs = 2)) %>% 
  bind_rows(pos3 %>% mutate(obs = 3))

ggplot(dat2, aes(x=samp)) +
  geom_col(aes(y=x2, fill=obs), color="black", alpha=0.5) +
  coord_flip() +
  scale_fill_gradient(low="steelblue", high="steelblue") +
  theme(legend.position = "none")