get_cor_matrix: Calculate and Visualize Correlation Matrix between Two...
In IOBR/IOBR: Immune Oncology Biological Research

get_cor_matrix

R Documentation

Calculate and Visualize Correlation Matrix between Two Variable Sets

Description

The "get_cor_matrix" function calculates and visualizes the correlation matrix between two sets of variables in a dataset. It provides flexibility in defining correlation methods, handling missing values, and incorporating additional data. The function supports various correlation methods, such as Pearson correlation, and displays the correlation result in a customizable plot. The plot includes color-coded tiles representing the correlation value between each pair of variables. Additionally, the function offers options to save the plot and data for further analysis.

Usage

get_cor_matrix(
  data,
  feas1,
  feas2,
  method = "pearson",
  path = NULL,
  index = 1,
  fig.type = "pdf",
  width = NULL,
  height = NULL,
  project = NULL,
  is.matrix = FALSE,
  scale = T,
  font.size.star = 8,
  font.size = 15,
  fill_by_cor = FALSE,
  round.num = 1
)

Arguments

`data`	The input dataset for correlation analysis. Genes or signatures in columns. If data is a matrix, please set 'is.matrix' = TRUE, and data will be t()
`feas1`	A vector of variable names representing the first set of variables for correlation analysis.
`feas2`	A vector of variable names representing the second set of variables for correlation analysis.
`method`	The method used to calculate correlation. Default is "pearson".
`path`	The path to save the correlation plot. If not specified, the plot will be saved in a folder named "index-cor_matrix_plot".
`index`	A numeric value used for naming the output plot file. Default is 1.
`fig.type`	The file format of the output plot. Default is "pdf".
`width`	The width of the output plot.
`height`	The height of the output plot.
`project`	The name of the project or analysis. This will be used as the plot title. Default is NULL.
`is.matrix`	A logical value indicating whether the input data is a matrix. Default is FALSE.
`scale`	A logical value indicating whether to scale the data before correlation analysis. Default is TRUE.
`font.size.star`	The font size of the significance stars in the plot. Default is 8.
`font.size`	The font size of the axis labels and tick marks in the plot. Default is 15.
`fill_by_cor`	A logical value indicating whether to fill the tiles in the plot according to the correlation values. Default is FALSE.
`round.num`	The number of decimal places to round the correlation values. Default is 1.