gemini_boxplot {gemini} | R Documentation

## 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)

[Package gemini version 1.6.0 Index]