Bios2cor (version 2.1)

scores.boxplot: 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=NULL, 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. Default is NULL (a BOXPLOT.png file will be created). 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.

Value

A pdf figure with boxplots to compare correlation/covariation scores

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.

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

# NOT RUN {
  #File path for output file
  wd <- tempdir()
  #wd <-getwd() 
  file <- file.path(wd,"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)

  #Creating MIP correlation object
  #mip <- mip(align, gap_ratio = 0.2)

  #Selecting correlation matrices
  omes <-omes$Zscore
  #mip <- mip$Zscore

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