gemini_boxplot: gemini_boxplot

In sellerslab/gemini: GEMINI: Variational inference approach to infer genetic interactions from pairwise CRISPR screens

gemini_boxplot

Description

A function to visualize the results of GEMINI over the raw data.

Usage

gemini_boxplot(
  Model,
  g,
  h,
  nc_gene = NULL,
  sample,
  show_inference = TRUE,
  color_x = FALSE,
  identify_guides = FALSE
)

Arguments

Model	a gemini.model object
g	a character naming a gene to visualize
h	a character naming another gene to visualize
nc_gene	a character naming the gene to use as a negative control, to be paired with each individual g and h. Defaults to Model$nc_gene.
sample	a character naming the sample to visualize
show_inference	a logical indicating whether to show the inferred individual or combined values for each gene/gene pair (default TRUE)
color_x	a logical indicating whether to visualize the sample-independent effects for each individual guide or guide pair (default FALSE)
identify_guides	a logical indicating whether to identify guides with unique colors and shapes (default FALSE)

Details

Raw LFC data is plotted for each gene combination ('g'-'nc_gene', 'h'-'nc_gene', 'g'-'h') in a standard boxplot. Horizontal green line segments are plotted over the box plots indicating the individual gene effects or the inferred total effect of a particular gene combination. Each guide pair can be colored based on the inferred sample independent effects g_i, h_j, and g_i,h_j. Additionally, colors and shapes can be used to distinguish unique guides targeting gene g and h, respectively.

Value

a ggplot2 object

Examples

data("Model", package = "gemini")

gemini_boxplot(Model, g = "BRCA2", h = "PARP1", nc_gene = "CD81", 
sample = "A549", show_inference = TRUE,
color_x = FALSE, identify_guides = FALSE)

sellerslab/gemini documentation built on Dec. 5, 2022, 8:56 a.m.