一种通过填充子集在堆叠条中排序 x 轴的整洁方法

Question

I have a dataframe GTs.df of genotypes for 8 genes across 8 different genetic lines . "NA" s represent ambiguous sequencing calls. (There are few heterozygotes "Aa" because these are inbred lines).

GTs.df <- data.frame(Gene = rep(c("Zm1","Zm2","Zm3","Zm4","Zm5","Zm6","Zm7","Zm8"), each=8),
  Line = rep(c("L1", "L2", "L3", "L4", "L5", "L6", "L7", "L8"), times = 8),
  Genotype = c(rep(c("aa", "Aa", "AA", "NA"), times = c(2, 1, 5, 0)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(4, 0, 1, 3)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(4, 1, 3, 0)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(3, 0, 4, 1)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(4, 0, 3, 1)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(5, 1, 2, 0)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(1, 0, 3, 4)),
               rep(c("aa", "Aa", "AA", "NA"), times = c(1, 1, 6, 0))
               )
  )

I want to compare the distribution of genotypes across the lines for each gene , so I make this stacked bar plot initially:

GTs.df %>%
  filter(Genotype != "NA") %>%
  mutate(Genotype = fct_relevel(Genotype, 
                                  c("AA", "Aa", "aa"))) %>%
  ggplot() +
  aes(x = Gene,
      fill = Genotype) +
  geom_bar(position = "stack",
           stat = "count") + 
  ylab("Number of Lines")

But the problem is that I want the Genes/columns ordered by number of "aa" so that it is more readable . I can reorder the Genes via fct_reorder as suggested by tbradley / 48748250/FilipW and demonstrated below...

GTs.df %>%
  filter(Genotype != "NA") %>%
  mutate(Genotype = fct_relevel(Genotype, 
                                  c("AA", "Aa", "aa")),
         Gene = fct_reorder(Gene,
                            as.numeric(Genotype),
                            .fun = mean)
         ) %>%
  ggplot() +
  aes(x = Gene,
      fill = Genotype) +
  geom_bar(position = "stack",
           stat = "count") + 
  ylab("Number of Lines")

As you can see, this does order the Genes/columns pretty well via sorting by proportion , but this is imperfect in this case because of missing data points and greater than 2 levels . You can see the last Gene (Zm2) has fewer "aa" lines than the Gene before it but does have a higher proportion/mean of "aa".

I also tried a variation of this using sum instead of mean .

GTs.df %>%
  filter(Genotype != "NA") %>%
  mutate(Genotype = fct_relevel(Genotype, 
                                  c("AA", "Aa", "aa")),
         Gene = fct_reorder(Gene,
                            as.numeric(Genotype),
                            .fun = sum)
         ) %>%
  ggplot() +
  aes(x = Gene,
      fill = Genotype) +
  geom_bar(position = "stack",
           stat = "count") + 
  ylab("Number of Lines")

It also almost works, but is still imperfect . Gene Zm4 has fewer "aa"s than the column before it, I guess because Zm4 has more total datapoints to contribute to the sum.

Ideally , I would want to use some sort of count function instead, but neither n or count work for me, no matter what class I change Genotype to. (Many combos so I spared the long, depressing list of error messages).

I did find a non-tidy solution from 48748250/talat that arranges the columns by count/absolute frequency of "aa" as desired :

gene_lvls <- names(sort(table(GTs.df[GTs.df$Genotype == "aa", "Gene"])))

GTs.df %>%
  filter(Genotype != "NA") %>%
  mutate(Genotype = fct_relevel(Genotype, 
                                  c("AA", "Aa", "aa"))) %>%
  ggplot() +
  aes(x = factor(Gene, 
                 levels = gene_lvls),
      fill = Genotype) +
  geom_bar(position = "stack",
           stat = "count") + 
  ylab("Number of Lines")

But I am hoping there's a tidy/dplyr/forcat-friendly way to achieve this, partly for learning/understanding and partly for pickiness/aethetic pleasure . Based on the number of similar forum questions, I have a feeling other people would be pleased by such a solution too. Bonus points if the solution has a secondary filter/tie-breaker when multiple columns have equal number of "aa" , as demonstrated by Zm2, Zm3 and Zm5 in the above plot.

Thank you in advance for your time and effort!

Here are some other forum pages that are somewhat related:

R ggplot2 Reorder stacked plot?

How to control ordering of stacked bar chart using identity on ggplot2

sort columns with categorical variables by numerical varables in stacked barplot

Answer 1

Here's one approach using fct_inorder after calculating some Gene-wise metrics like # of aa an total number of lines. This provides a pretty flexible way of creating whatever sorting metric you want, which could involve multiple tie-breakers.

GTs.df %>%
  filter(Genotype != "NA") %>%
  mutate(Genotype = fct_relevel(Genotype, 
                                c("AA", "Aa", "aa"))) %>%
  group_by(Gene) %>%
  mutate(num_aa = sum(Genotype == "aa"),
         ttl_lines = n()) %>%
  ungroup() %>%
  arrange(num_aa, ttl_lines) %>%        # Define your tie-breakers here
  mutate(Gene = fct_inorder(Gene)) %>%  # Assign factor in order of appearance 
  
  ggplot() +
  aes(x = Gene,
      fill = Genotype) +
  geom_bar(position = "stack",
           stat = "count") + 
  ylab("Number of Lines")