In tidymass/massdataset: massdataset

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  warning = FALSE,
  message = TRUE,
  out.width = "100%"
)

For one mass_dataset class object, we can get the summary information of it.

Data preparation

library(massdataset)
library(tidyverse)

data("expression_data")
data("sample_info")
data("variable_info")

object =
  create_mass_dataset(
    expression_data = expression_data,
    sample_info = sample_info,
    variable_info = variable_info
  )

Summary information

Just type this object in the R session.

object

We can just basic information of the object.

Use functions to get the summary information

##dim of object
dim(object)
##row number
nrow(object)
##column number
ncol(object)
##sample number
get_sample_number(object)
#variable number
get_variable_number(object)

##sample id
colnames(object)
##variable id
rownames(object) %>% 
  head()
##sample id
get_sample_id(object)
##variable id
get_variable_id(object) %>% 
  head()

Explore

###show mz rt plot
object %>%
  show_mz_rt_plot()
###should log
object %>%
  `+`(1) %>% 
  log(10) %>%
  show_mz_rt_plot()
###use hex
object %>%
  show_mz_rt_plot(hex = TRUE)

Missing values

##show missing values plot
show_missing_values(object)

show_missing_values(object[1:10,], cell_color = "white")

###only show subject samples
object %>%
  activate_mass_dataset(what = "sample_info") %>%
  filter(class == "Subject") %>%
  show_missing_values()

###only show QC samples
object %>%
  activate_mass_dataset(what = "expression_data") %>%
  dplyr::select(contains("QC")) %>%
  show_missing_values()

###only show features with mz < 100
object %>%
  activate_mass_dataset(what = "variable_info") %>%
  dplyr::filter(mz < 100) %>%
  show_missing_values(cell_color = "white",
                      show_row_names = TRUE,
                      row_names_side = "left")

##show missing values plot
show_sample_missing_values(object)
show_sample_missing_values(object, color_by = "class")
show_sample_missing_values(object, color_by = "class", order_by = "na")
show_sample_missing_values(object, color_by = "class", order_by = "na",
                           desc = TRUE)

##show missing values plot
show_variable_missing_values(object)
show_variable_missing_values(object, color_by = "mz")

show_variable_missing_values(object, color_by = "rt") +
  scale_color_gradient(low = "skyblue", high = "red") 

show_variable_missing_values(object, color_by = "mz", 
                             order_by = "na")
show_variable_missing_values(object, color_by = "mz", 
                             order_by = "na",
                           desc = TRUE, percentage = TRUE)