scores.boxplot: Creates boxplots of correlation/covariation scores

In Bios2cor: From Biological Sequences and Simulations to Correlation Analysis

Creates boxplots of correlation/covariation scores

Description

Given a list of correlation/covariation matrices, build boxplots for comparative purposes.

Usage

  scores.boxplot(corr_matrix_list, name_list, filepathroot, elite=25, high=275)

Arguments

corr_matrix_list	A list of correlation/covariation matrices to be compared
name_list	The names of the correlation/covariation matrices
filepathroot	The root of the full path name for the output file. if NULL, a BOXPLOT.png file will be created in tempdir(). If not NULL, the "_BOXPLOT.png" extension is added to the filepathroot.
elite	An integer to determine the number of pairs with the highest and lowest scores (e.g. 25: pairs ranked 1 to 25 in decreasing or increasing order) to be colored with the "elite" color codes. Default is 25.
high	An integer to determine the number of pairs with the next highest and lowest scores (e.g. 275: pairs ranked 26 to 275 in decreasing or increasing order) to be colored with the "high" color codes. Default is 275.

Details

The correlation/covariation matrices contain the correlation/covariation scores for each pair of elements [i,j]. The boxplots will allow comparing these scores using color codes : the highest values are dark blue, the next highest values are light blue, the lowest values are red and the next lowest values are pink.

Value

A pdf figure with boxplots to compare correlation/covariation scores

Author(s)

Julien PELE and Antoine GARNIER

References

For an application of these boxplots, see :

Pele J, Abdi H, Moreau M, Thybert D and Chabbert M (2011) Multidimensional scaling reveals the main evolutionary pathways of class A G-protein-coupled receptors. PLoS ONE 6: e19094. doi:10.1371.

Examples

  #File path for output file
  out <- tempdir()
  file <- file.path(out,"test_seq") 

  #Importing MSA file
  msf <- system.file("msa/toy_align.msf", package = "Bios2cor")
  align <- import.msf(msf)

  #Creating OMES correlation object
  omes <- omes(align, gap_ratio = 0.2)

  #Selecting correlation matrices
  omes <-omes$Zscore

  #Creating a list of matrices and plotting the boxplots in a graph
  #One matrix
  corr_matrix_list <- list(omes)
  name <- c("omes")
  scores.boxplot(corr_matrix_list, name, file, 25, 275)

Bios2cor documentation built on April 4, 2025, 4:14 a.m.