M19: M19 data analysis tools.

#'SigStack


#' @author Hannah Hayman, \email{l.hayman.1@@research.gla.ac.uk}
#' This function takes DMG signatures for X number of comparisons and stacks them for easy visualisation.


#' @import tidyverse
#' @import ggpubr
#' @import ggplot2


#' @param Subdirectory A subdirectory of your working directory, in which you store your comparison files.
#' @param OutputFileName A name for your final outpt file.
#' @param ORlow The lower boundary for your OR. DMGs with an odds ratio between this value and your ORhigh will be excluded.Default value is 0.5.
#' @param ORhigh The upper boundary for your OR. DMGs with an odds ratio between this value and your ORlow will be excluded.Default value is 2.
#' @param pval Your chosen cut off for 'statistical significance'. Default value is 0.05.
#' @param Palette Choose your colour palette; greyscale, blue, red, pink, green. Default palette is greyscale.


#' @return Returns a matrix plot, stacking mutational signatures generated from the input comparison files.


#' @examples SigStack(Subdirectory = "Files", OutputFileName = "", ORlow = "0.5", ORhigh = "2", pval = "0.1", Palette = "Pink")


#' @export




#Function
SigStack <-
  function(Subdirectory = "",
           OutputFileName = "MutSigStack",
           ORlow = "0.5",
           ORhigh = "2",
           pval = "0.05",
           Palette = "Greyscale",
           xlab = "10") {
    #Check input for errors
    Colours = c("Greyscale", "Blue", "Red", "Green", "Pink")
    if (!all(Palette %in% Colours))
      stop(
        "Incompatible input for 'Palette'. Available colours schemes are; Greyscale, Red, Pink, Blue and Green."
      )



    #Alter working directory
    WD <- getwd()
    if (file.exists(Subdirectory)) {
      setwd(Subdirectory)
    } else {
      stop(
        'Incompatible subdirectory. Please check the name of the folder containing your files.It should be a subdirectory within your working directory.'
      )
    }


    on.exit(setwd(WD), add = TRUE)



    #Read and rename data files
    filenames <- gsub("\\.csv$", "", list.files(pattern = "\\.csv$"))
    DataFrames <-
      lapply(list.files(pattern = "\\.csv$"), read.csv, sep = ";")
    names(DataFrames) <- filenames
    setwd(WD)


    for (i in 1:length(filenames)) {
      DataFrames[[filenames[i]]]$or <-
        as.numeric(gsub(",", ".", gsub("\\.", "", DataFrames[[filenames[i]]]$or)))
      DataFrames[[filenames[i]]]$pval <-
        as.numeric(gsub(",", ".", gsub("\\.", "", DataFrames[[filenames[i]]]$pval)))
    }


    #Change infinite ORs to a value of '2'
    for (i in 1:length(filenames)) {
      DataFrames[[filenames[i]]]$or <-
        ifelse(DataFrames[[filenames[i]]]$or == "Inf", 2, DataFrames[[filenames[i]]]$or)
      DataFrames[[filenames[i]]]$or <-
        ifelse(DataFrames[[filenames[i]]]$or == "0", 0.00000001, DataFrames[[filenames[i]]]$or)
    }


    #Select cases within parameters of chosen OR and p value
    for (i in 1:length(filenames)) {
      DataFrames[[filenames[i]]] <-
        DataFrames[[filenames[i]]][which(
          DataFrames[[filenames[i]]]$or >= as.numeric(ORhigh) &
            DataFrames[[filenames[i]]]$pval <= as.numeric(pval) |
            DataFrames[[filenames[i]]]$or <= as.numeric(ORlow) &
            DataFrames[[filenames[i]]]$pval <= as.numeric(pval)
        ),]
    }



    #Check for empty dataframes
    DeletedDataFrames <- list()
    Rows <- 1
    for (i in 1:length(filenames)) {
      if (nrow(DataFrames[[filenames[i]]]) == 0) {
        Rows <- 0
        DeletedDataFrames <- c(DeletedDataFrames, filenames[i])
        # # DataFrames[[filenames[i]]] <- NULL
        # # filenames[i] <- NULL
        # DataFrames = DataFrames[names(DataFrames) != (DataFrames[[filenames[i]]])]
        # FileNames = Filenames != filenames[i]
      }
    }


    if (Rows == 0) {
      stop(
        paste(
          "The following datasets had no viable genes after filtering by OR and p value; ",
          DeletedDataFrames,
          ". Please remove them from analysis."
        )
      )
    }


    #Variables cut down to genes, odds ratio and p value
    Variables <- c("Hugo_Symbol", "or", "pval")
    for (i in 1:length(filenames)) {
      DataFrames[[filenames[i]]] <- DataFrames[[filenames[i]]][Variables]
    }


    #Append 'Compartment' variable
    for (i in 1:length(filenames)) {
      DataFrames[[filenames[i]]]$Compartment <- filenames[i]
    }


    #Rearrange order of variables
    for (i in 1:length(filenames)) {
      DataFrames[[filenames[i]]] <-
        DataFrames[[filenames[i]]][c("Compartment", "Hugo_Symbol", "or")]
    }


    #Merging data frames
    Merge1 = do.call(rbind, DataFrames)
    Merge2 <- tidyr::spread(Merge1, Hugo_Symbol, or, fill = 0)
    Data <- tidyr::gather(Merge2, Hugo_Symbol, or,-Compartment)



    #Coding of odds ratio
    Data$or_coded <- Data$or
    Data$or_coded <- ifelse(Data$or_coded > 1, 1, Data$or_coded)
    Data$or_coded <-
      ifelse(Data$or_coded < 1 & Data$or_coded > 0, 0.5, Data$or_coded)
    names(Data)[names(Data) == "or_coded"] <- "Odds_Ratio"




    #Define colour scheme
    if (Palette == "Greyscale") {
      MapColours <- c("slategrey", "black", "white")
    }

    if (Palette == "Red") {
      MapColours <- c("firebrick1", "firebrick4", "white")
    }

    if (Palette == "Pink") {
      MapColours <- c("deeppink", "deeppink4", "white")
    }

    if (Palette == "Green") {
      MapColours <- c("darkolivegreen1", "darkgreen", "white")
    }

    if (Palette == "Blue") {
      MapColours <- c("deepskyblue", "dodgerblue4", "white")
    }




    #Generation of plot
    SigStackPlot <-
      ggplot(data = Data, aes(x = Hugo_Symbol, y = Compartment)) +
      geom_tile(aes(fill = factor(Odds_Ratio))) +
      scale_fill_manual(
        values = MapColours,
        name = "Odds_Ratio",
        limits = c("0.5", "1", "0"),
        labels = c(paste("OR <", ORlow, sep = " "), paste("OR >", ORhigh, sep = " "), "")
      ) +
      labs(
        title = "Mutational Signatures by Lymphocyte Compartment",
        subtitle = "",
        y = "Lymphocyte Compartment",
        x = "Gene",
        tag = ""
      ) +
      theme(
        panel.background = element_rect(fill = "white", colour = "white"),
        axis.line = element_line(
          size = 0.5,
          linetype = "solid",
          colour = "white"
        )
      ) +
      theme(plot.title = element_text(
        face = "bold",
        colour = "black",
        size = 15,
        hjust = 0.5
      )) +
      theme(axis.title.x = element_text(
        face = "bold",
        colour = "black",
        size = 12
      )) +
      theme(axis.text.x = element_text(
        colour = "black",
        size = xlab,
        angle = 90,
        vjust = 0.5,
        hjust = 1
      )) +
      theme(
        axis.title.y = element_text(
          face = "bold",
          colour = "black",
          size = 12,
          angle = 90,
          vjust = 0.5,
          hjust = 0.5
        )
      ) +
      theme(axis.text.y = element_text(
        colour = "black",
        size = 10,
        vjust = 0.5,
        hjust = 1
      )) +
      theme(legend.title = element_text(
        face = "bold",
        colour = "black",
        size = 12
      )) +
      theme(legend.text = element_text(
        colour = "black",
        size = 10,
        vjust = 0.5,
        hjust = 1
      )) + theme(legend.text.align = 0)






    #Printing of plot to TIFF
    tiff(paste(OutputFileName, ".tiff", sep = ""),
         width = 1000,
         height = 300)
    print(SigStackPlot)
    dev.off()
    #print(SigStackPlot)







    message(
      "Wonder Woman hopes that you enjoy your stacked mutational signatures. Your plot is in your working directory. Blessings of Gaea be with you :)"
    )


  }