Analysis on categorical cell metadata of CZ CELLxGENE Discover
This notebook is only used to create the figures and tables. Results are discussed here.
Reading data
Load the data generated by “TODO insert link to code that generated data”
n_categories <- read_tsv("./n_categories.tsv") %>%
arrange(-n_col_two_or_more_category)##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## exp_url = col_character(),
## n_col_one_category = col_double(),
## n_col_two_or_more_category = col_double(),
## largest_category_n = col_double(),
## largest_category_label = col_character()
## )n_categories$exp_url <- gsub("cellxgene.dev.single-cell.czi.technology","cellxgene.cziscience.com", n_categories$exp_url)
category_counts <- read_tsv("./category_counts.tsv") %>%
arrange(n_categories) ##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## n_categories = col_double(),
## counts = col_double()
## )category_counts <- category_counts[category_counts$n_categories > 1, ]Analysis
Histogram of number columns that have x number of categories. A column is a cell metadata column (e.g. “Sex”) and a category is the possible values that exist (e.g. “Male”, “Female”, “Unknown”)
ggplot(head(category_counts, 80), aes(x = as.factor(n_categories), y = counts)) +
geom_bar(stat = "identity") +
labs(title = "Histogram of category counts per cell metadata column", subtitle = paste("Max number of categories is ", max(category_counts$n_categories))) +
xlab("Number of categories in column") +
ylab("Cell metadata column counts") +
theme_bw()
Table, each row is a dataset. The columns are:
- Number of columns w/ 1 cat: number of cell metadata columns that only have 1 category.
- Number of columns w/ > 1 cat: number of cell metadata columns that have more than 1 category.
- Column with highest cats: the column that has the highest number of categories.
- N cats for column with highest cat n: the number of categories of previous column.
n_categories %>%
dplyr::rename(`Number of columns w/ 1 cat` = n_col_one_category,
`Number of columns w/ > 1 cat` = n_col_two_or_more_category,
`Column with highest cats` = largest_category_label,
`N cats for column with highest cat n` = largest_category_n
) %>%
head(40) %>%
kbl() %>%
kable_paper("hover", full_width = T)n_categories %>%
arrange(-largest_category_n) %>%
dplyr::rename(`Number of columns w/ 1 cat` = n_col_one_category,
`Number of columns w/ > 1 cat` = n_col_two_or_more_category,
`Column with highest cats` = largest_category_label,
`N cats for column with highest cat n` = largest_category_n
) %>%
head(40) %>%
kbl() %>%
kable_paper("hover", full_width = T)