R/plotPairwise.R

In elulu3/LymphoSeqTest: Analyze high-throughput sequencing of T and B cell receptors

#' Pairwise comparison plot
#' 
#' Creates a heat map from a Bhattacharyya, Similarity, Sorensen, or PSI matrix.
#' 
#' @param matrix A Bhattacharyya, Similarity, Sorensen, or PSI matrix produced
#' by the LymphoSeq2 scoringMatrix function.
#' @return A pairwise comparison heat map.
#' @details The plot is made using the package ggplot2 and can be reformatted
#' using ggplot2 functions.  See examples below.
#' @seealso An excellent resource for examples on how to reformat a ggplot can 
#' be found in the R Graphics Cookbook online (\url{http://www.cookbook-r.com/Graphs/}).
#' The functions to create the similarity or Bhattacharyya matrix can be found 
#' here: \code{\link{similarityMatrix}} and \code{\link{bhattacharyyaMatrix}}
#' @examples
#' file_path <- system.file("extdata", "TCRB_sequencing", package = "LymphoSeq2")
#' 
#' stable <- readImmunoSeq(path = file_path)
#' 
#' atable <- productiveSeq(stable, aggregate = "junction_aa")
#' 
#' similarity_matrix <- scoringMatrix(productive_table = atable, mode="Similarity")
#' 
#' pairwisePlot(matrix = similarity_matrix)
#' 
#' bhattacharyya_matrix <- scoringMatrix(productive_table = atable, mode="Bhattacharyya")
#' 
#' pairwisePlot(matrix = bhattacharyya_matrix)
#' 
#' # Change plot color, title legend, and add title
#' pairwisePlot(matrix = similarity_matrix) + 
#' ggplot2::scale_fill_gradient(low = "#deebf7", high = "#3182bd") + 
#' ggplot2::labs(fill = "Similarity score") + 
#' ggplot2::ggtitle("Figure Title")
#' @export
#' @import tidyverse
pairwisePlot <- function(matrix) {
    samples <- rownames(matrix)
    matrix[base::lower.tri(matrix)] <- NA
    matrix <- matrix %>% 
              tibble::as_tibble() %>%
              dplyr::mutate(repertoire_id = samples) %>%
              dplyr::select(repertoire_id, dplyr::everything()) %>%
              tidyr::pivot_longer(-repertoire_id, names_to = "repertoire_id_y", values_to = "score", values_drop_na = TRUE) %>%
              dplyr::arrange(repertoire_id, repertoire_id_y)
    ggplot(data = matrix, aes_string(x = "repertoire_id", y = "repertoire_id_y", fill = "score")) + 
    ggplot2::geom_tile() + 
    ggplot2::geom_text(aes(repertoire_id, repertoire_id_y, label = sprintf("%0.2f", round(score, digits = 2))), color = "black", size = 4) +
    ggplot2::scale_fill_gradient(low = "#fee8c8", high = "#e34a33") + 
    ggplot2::theme_classic() + 
    ggplot2::labs(x = "", y = "", fill = "") + 
    ggplot2::scale_y_discrete(limits = rev(levels(as.factor(matrix$repertoire_id_y)))) +
    ggplot2::theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))
}