cell_bar_plot: Visualize the results as a stacked bar chart with...

In IOBR/IOBR: Immune Oncology Biological Research

Visualize the results as a stacked bar chart with tidyverse/ggplot2.

Description

cell_bar_plot() provides batch visualization of tumor microenvironment (TME) cell fractions. It supports input from deconvolution results generated by methodologies such as 'CIBERSORT', 'EPIC', and 'quanTIseq'. The function enables comparison of TME cell distributions within one sample or among different samples.

Usage

cell_bar_plot(
  input,
  id = "ID",
  title = "Cell Fraction",
  features = NULL,
  pattern = NULL,
  legend.position = "bottom",
  coord_filp = TRUE,
  palette = 3,
  show_col = F,
  cols = NULL
)

Arguments

input	input result of 'CIBERSORT' or 'quantiseq'
id	patient identifier of input
title	plot title
features	default is NULL, user can define which column to draw
pattern	patterns of features
legend.position	legend position
coord_filp	logical variables, 'coord_filp' of ggplot2
palette	default is palette3
show_col	default is FALSE
cols	default is NULL, user can define colors manually

Value

A ggplot2 object representing the bar plot of cell fractions.

Examples

# Loading TCGA-STAD microenvironment data
data("sig_stad", package = "IOBR")
# showing 20 tumor microenvironment cell proportion deconvoluted by CIBERSORT algorithm
cell_bar_plot(input = sig_stad[1:20, ], id = "ID", features = colnames(sig_stad)[25:46])

IOBR/IOBR documentation built on Sept. 9, 2024, 8:36 p.m.