count.violin: Count Distribution

In christensensm/COMPOSE: Calculation and Visualization of Phenotypic CRISPR Screens

Description

Violin plot visualizing read distribution

Usage

count.violin(
  countsTable,
  metadata,
  identifier1 = "sample",
  identifier2 = NULL,
  transform = FALSE,
  cpm = FALSE,
  save = F
)

Arguments

countsTable	input matrix containing normalized gRNA counts with gRNA ids as row names
metadata	input dataframe containing sample names and other identifiers or data
identifier1	string identifying column name of metadata with which to adjust color in violin plot
identifier2	string identifying column name of metadata with which to adjust alpha in violin plot
transform	logical - do you want to log10 transform the counts
cpm	logical - do you want to normalize the counts by sequencing depth
save	logical - do you want to save the violin plot to pdf

Value

ggplot object of the violin plot

See Also

ggplot which this function uses to plot

Examples

y <- matrix(rnorm(100*9, mean = 10, sd = 1),100,9)
colnames(y) <- paste0('sample.',1:9)
metadata <- data.frame(sample = paste0('sample.',1:9), batch = c("A","A","A","B","B","B","C","C","C"),
time = rep(c(1,2,3),times = 3))
count.violin(y, metadata, identifier1 = 'sample', identifier2='time', transform = T)
...

christensensm/COMPOSE documentation built on Dec. 22, 2020, 3:43 a.m.