counts_boxplot: Quickly plot a boxplot of counts

In latlio/tidyde: Tidy Differential Expression

Description

'counts_boxplot()' generates a boxplot of counts given count data.

Usage

counts_boxplot(
  count_df,
  metadata,
  sample_var,
  facet_var = NULL,
  .y_intercept = 2e+06
)

Arguments

count_df	cleaned dataframe of counts, rows should be gene IDs, columns should be samples, cells should only contain counts. Also accepts a 'DGEList' object
metadata	cleaned metadata for RNAseq data
sample_var	variable of sample ids
facet_var	variable to facet plots by
.y_intercept	default 2000000, setting to NULL removes horizontal line

Details

Like any other ggplot object, you can customize the theme of the plot. Note that this function generates a fairly generic boxplot, and thus is intended for quick exploratory purposes (much like the intention behind 'qplot()').

Value

a boxplot of RNAseq counts (ggplot object)

Examples

counts <- readr::read_delim("data/GSE60450_Lactation-GenewiseCounts.txt", delim = "\t")
meta <- readr::read_delim("data/SampleInfo_Corrected.txt", delim = "\t") %>%
  mutate(FileName = stringr::str_replace(FileName, "\\.", "-"))
mycount <- check_sample_names(counts, c(1,2), meta, FileName) %>%
  purrr::pluck("mod_count")
mymeta <- check_sample_names(counts, c(1,2), meta, FileName) %>%
  purrr::pluck("meta")

# View total raw counts
counts_boxplot(mycount, mymeta, SampleName)

# View filtered counts and also facet by variable
id <- as.character(counts$EntrezGeneID)
mycount %>%
  filter_genes(., id, "edgeR") %>%
  counts_boxplot(., mymeta, SampleName, CellType)

# As an EDA step within a pipeline of functions
my_design <- check_sample_names(counts, c(1,2), meta, FileName) %>%
  purrr::pluck("meta") %>%
  make_design_matrix(., c("Status"))

check_sample_names(counts, c(1,2), meta, FileName) %>%
  purrr::pluck("mod_count") %>%
  filter_genes(., id, "edgeR") %T>%
  {print(counts_boxplot(., check_sample_names(counts, c(1,2), meta, FileName) %>%
    purrr::pluck("meta"), SampleName))} %>%
  make_voom(., my_design) %>%
  model_limma() %>%
  make_contrasts(design_matrix = my_design, Statuspregnant, Statusvirgin) %>%
  model_bayes()

latlio/tidyde documentation built on Dec. 21, 2021, 9:40 a.m.