R/mirrorPlotRACER.R

Defines functions mirrorPlotRACER

Documented in mirrorPlotRACER

#' Mirror Plot -- Regional Association ComparER Plot
#'
#' This function allows you to creat a plot of -log10(P-values) for two sets of association data.
#' Mirror plots illustrate the two associations on a common x-axis, with the first association
#' inverted, mirroring the two associations against one another.
#'
#' @param assoc_data1 required. A dataframe that has columns named POS representing the position
#' of the SNP on the chromosome, LOG10P which contains the -log10(P-values), CHR, which contains
#' the chromosome number, RS_ID, which contains LD information. If your data set has been processed
#' using the formatRACER function and the ldRACER function, these columns will be appropriately
#' named in your data.
#' @param assoc_data2 required. identifcal in format to assoc_data1
#' @param chr required. chromosome you wish to plot
#' @param build optional. indicates the genome build to use to plot the genes below the association plot. default = "hg19", but can be changed to "hg38"
#' @param set optional. default = "protein_coding", however can be set to "all" to plot all RNAs in the genome
#' @param name1 optional. name of association set 1
#' @param name2 optional. name of association set 2
#' @param plotby required. "coord", "gene", or "snp". Which parameter to use to
#' determine the reigon to be plotted.
#' @param gene_plot optional. If "gene" selected for plotby, then plot will be +/- 50kb of gene, should be a human gene symbol
#' @param snp_plot optional. If "snp" selected for plotby, then plot will be +/- 50kb of snp
#' @param start_plot optional. If "coord" selected for plotby, then this will be lower bound of x-axis
#' @param end_plot optional. If "coord" selected for plotby, then this will be upper bound of x-axis
#' @param label_lead optional. default = FALSE, set = TRUE if you wish to add a label to your graph of the SNP used to calculate LD. If the SNP used to calculate LD is not in your data set, the SNP with the greatest -LOG10(P) will be labeled. Labels both plots.
#'
#' @keywords association plot
#' @export
#' @import ggplot2
#' @examples
#' \dontrun{
#' data(mark3_bmd_gwas)
#' data(mark3_eqtl)
#'
#' mark3_bmd_gwas_f = RACER::formatRACER(assoc_data = mark3_bmd_gwas, chr_col = 3,
#' pos_col = 4, p_col = 11)
#' mark3_eqtl_f = RACER::formatRACER(assoc_data = mark3_eqtl, chr_col = 10,
#' pos_col = 11, p_col = 7)
#'
#' mark3_bmd_gwas_f_ld = RACER::ldRACER(assoc_data = mark3_bmd_gwas_f,
#' rs_col = 2, pops ="EUR", lead_snp = "rs11623869")
#' mark3_eqtl_f_ld = RACER::ldRACER(assoc_data = mark3_eqtl_f,
#' rs_col = 15, pops = "EUR", lead_snp = "rs11623869")
#' mirrorPlotRACER(assoc_data1 = mark3_bmd_gwas_f_ld, assoc_data2 = mark3_eqtl_f_ld,
#' chr = 14, plotby = "gene", gene_plot = "MARK3")}

mirrorPlotRACER <- function(assoc_data1, assoc_data2, chr, build = "hg19", set = "protein_coding", name1="Association Dataset #1", name2="Association Dataset #2", plotby, gene_plot=NULL, snp_plot=NULL, start_plot=NULL, end_plot=NULL, label_lead = FALSE){
  reqs = c("CHR", "POS", "LOG10P")
  cols_1 = colnames(assoc_data1)
  cols_2 = colnames(assoc_data2)
  if(sum(reqs %in% cols_1) == 3){
  }else{stop("Association Data Set #1 is missing a required column.")}
  if(sum(reqs %in% cols_2) == 3){
  }else{stop("Association Data Set #2 is missing a required column.")}

  if(build == "hg38"){
    utils::data(hg38)
    chr_in = chr
    colnames(hg38) = c("GENE_ID", "CHR", "TRX_START", "TRX_END", "LENGTH", "GENE_NAME", "TYPE")
    gene_sub = hg38[hg38$CHR == chr_in,]
  }else if(build == "hg19"){
    utils::data(hg19)
    chr_in = chr
    colnames(hg19) = c("GENE_ID", "CHR", "TRX_START", "TRX_END", "LENGTH", "GENE_NAME", "TYPE")
    gene_sub = hg19[hg19$CHR == chr_in,]
  }

  if(set == "protein_coding"){
    gene_sub = gene_sub[gene_sub$TYPE == "protein_coding",]
  }else{
    gene_sub = gene_sub
  }

  `%>%` <- magrittr::`%>%`

  if((sum(is.null(plotby)) == 0) == TRUE){
    message("Plotting by...")
    if((plotby == "coord") == TRUE){
      message("coord")
      start = start_plot
      end = end_plot
    }else if((plotby == "gene") == TRUE){
      message(paste("gene:",gene_plot))
      if(sum(is.null(gene_plot)) == 0){
        p = subset(gene_sub, gene_sub$GENE_NAME == gene_plot)
        start = min(p$TRX_START) - 500000
        end = max(p$TRX_END) + 500000
        }else{stop("No gene specified.")}
    }else if((plotby == "snp") == TRUE){
      message(paste("snp",snp_plot))
      q = assoc_data1[assoc_data1$RS_ID == snp_plot,]
      w = q$POS
      w = as.numeric(as.character(w))
      start = w - 500000
      end = w + 500000}
  }else{
    stop("Please specify a parameter to plotby.")
  }

  # reading in gene data
  gene_sub = subset(gene_sub, gene_sub$TRX_START > (start-5000))
  gene_sub = subset(gene_sub, gene_sub$TRX_END < (end+5000))
  myCol = paste0("desc(", "LENGTH)")
  gene_sub %>%
    dplyr::arrange_(.dots = c(myCol))
  gene_sub = gene_sub[!duplicated(gene_sub$GENE_ID),]
  gene_sub = gene_sub[,c(3,4,6)]
  gene_sub = reshape2::melt(gene_sub, id.vars = "GENE_NAME")
  gene_sub$y_value = as.numeric(as.factor(gene_sub$GENE_NAME))
  plot_lab = subset(gene_sub, gene_sub$variable == "TRX_END")

  # read in, format, and filter data sets
  message("Reading in association data")
  in.dt <- as.data.frame(assoc_data1)
  in.dt$POS = as.numeric(as.character(in.dt$POS))
  in.dt$LOG10P = as.numeric(as.character(in.dt$LOG10P))
  in.dt$CHR = as.numeric(as.character(in.dt$CHR))
  in.dt = dplyr::filter_(in.dt, ~CHR == chr_in)
  in.dt = dplyr::filter_(in.dt, ~POS > start)%>%
    dplyr::filter_(~POS < end)

  if(label_lead == TRUE){
    lsnp_row_1 = which(in.dt$LABEL == "LEAD")
    label_data_1 = in.dt[lsnp_row_1,]
    if(dim(label_data_1)[1] == 0){
      lsnp_row_1 = in.dt[in.dt$LOG10P == max(in.dt$LOG10P),]
      label_data_1 = lsnp_row_1[1,]
    }
  }

  in.dt.2 <- as.data.frame(assoc_data2)
  in.dt.2$POS = as.numeric(as.character(in.dt.2$POS))
  in.dt.2$LOG10P = as.numeric(as.character(in.dt.2$LOG10P))
  in.dt.2$CHR = as.numeric(as.character(in.dt.2$CHR))
  in.dt.2 = dplyr::filter_(in.dt.2, ~CHR == chr_in)
  in.dt.2= dplyr::filter_(in.dt.2, ~POS > start)%>%
    dplyr::filter_(~POS < end)

  if(label_lead == TRUE){
    lsnp_row_2 = which(in.dt.2$LABEL == "LEAD")
    label_data_2 = in.dt.2[lsnp_row_2,]
    if(dim(label_data_2)[1] == 0){
      lsnp_row_2 = in.dt.2[in.dt.2$LOG10P == max(in.dt.2$LOG10P),]
      label_data_2 = lsnp_row_2[1,]
    }
  }

  len1 = nchar(trunc(max(in.dt$LOG10P)))
  len2 = nchar(trunc(max(in.dt.2$LOG10P)))

  scaleFUN0 <- function(x) sprintf("%.0f", x)
  scaleFUN1 <- function(x) sprintf("%.1f", x)
  scaleFUN2 <- function(x) sprintf("%.2f", x)
  scaleFUN3 <- function(x) sprintf("%.3f", x)
  scaleFUN4 <- function(x) sprintf("%.4f", x)

  # generate mirror plot
  message("Generating plot.")
  if("LD" %in% cols_1 && "LD_BIN" %in% cols_1){
    a = ggplot2::ggplot(data = in.dt, ggplot2::aes_string(x = "POS", y = "LOG10P", color = "LD_BIN")) +
      ggplot2::geom_point() + ggplot2::scale_colour_manual(
        values = c("1.0-0.8" = "red", "0.8-0.6" = "darkorange1", "0.6-0.4" = "green1",
                   "0.4-0.2" = "skyblue1", "0.2-0.0" = "navyblue", "NA" = "grey"), drop = FALSE) +
      ggplot2::theme_bw() + ggplot2::xlab(paste0("Chromosome ", chr_in, " Position")) + ggplot2::ylab("-log10(p-value)") +
      ggplot2::scale_y_reverse() + ggplot2::theme(axis.title.x=ggplot2::element_blank(),
                                axis.text.x=ggplot2::element_blank(),
                                axis.ticks.x=ggplot2::element_blank()) +
      ggplot2::theme(legend.position = "none") +
      ggplot2::xlim(start,end) + ggplot2::ggtitle(paste0(name1)) +
      theme(plot.title = element_text(size = 10, vjust = -1)) +
      theme(plot.margin = margin(5.5,5.5,-3,5.5))
  }else{
    message("No LD information for dataset #1.")
    a = ggplot2::ggplot(in.dt, ggplot2::aes_string(x = "POS", y = "LOG10P")) +
      ggplot2::geom_point() + ggplot2::theme_bw() + ggplot2::xlab(paste0("Chromosome ", chr_in, " Position")) +
      ggplot2::ylab("-log10(p-value)") +
      ggplot2::scale_y_reverse() + ggplot2::theme(axis.title.x=ggplot2::element_blank(),
                                                  axis.text.x=ggplot2::element_blank(),
                                                  axis.ticks.x=ggplot2::element_blank()) +
      ggplot2::theme(legend.position = "none") +
      ggplot2::xlim(start,end) + ggplot2::ggtitle(paste0(name1)) +
      theme(plot.title = element_text(size = 10, vjust = -1)) +
      theme(plot.margin = margin(5.5,5.5,-3,5.5))
  }

  if("LD" %in% cols_2 && "LD_BIN" %in% cols_2){
    b = ggplot2::ggplot(data = in.dt.2, ggplot2::aes_string(x = "POS", y = "LOG10P", color = "LD_BIN")) +
      ggplot2::geom_point() + ggplot2::scale_colour_manual(
        values = c("1.0-0.8" = "red", "0.8-0.6" = "darkorange1", "0.6-0.4" = "green1",
                   "0.4-0.2" = "skyblue1", "0.2-0.0" = "navyblue", "NA" = "grey"), drop = FALSE) +
      ggplot2::theme_bw() + ggplot2::xlab(paste0("Chromosome ", chr_in, " Position (Mbp)")) +
      ggplot2::ylab("-log10(p-value)") + ggplot2::theme(legend.position = "bottom") +
      ggplot2::xlim(start,end) + ggplot2::ylim(min(in.dt.2$LOG10P),max(in.dt.2$LOG10P)) +
      ggplot2::theme(axis.title.x=ggplot2::element_blank(),
                     axis.text.x=ggplot2::element_blank(),
                     axis.ticks.x=ggplot2::element_blank()) + ggplot2::ggtitle(paste0(name2)) +
      theme(plot.title = element_text(size = 10, vjust = -1))
    }else{
      b = ggplot2::ggplot(in.dt.2, ggplot2::aes_string(x = "POS", y = "LOG10P")) +
        ggplot2::geom_point() + ggplot2::theme_bw() + ggplot2::xlab(paste0("Chromosome ", chr_in, " Position (Mbp)")) +
        ggplot2::ylab("-log10(p-value)") + ggplot2::theme(legend.position = "bottom") +
        ggplot2::xlim(start,end) + ggplot2::ylim(min(in.dt.2$LOG10P),max(in.dt.2$LOG10P)) +
        ggplot2::theme(axis.title.x=ggplot2::element_blank(),
                       axis.text.x=ggplot2::element_blank(),
                       axis.ticks.x=ggplot2::element_blank()) + ggplot2::ggtitle(paste0(name1)) +
        theme(plot.title = element_text(size = 10, vjust = -1))
  }

    c = ggplot2::ggplot(gene_sub, ggplot2::aes_string(x = "value", y = "y_value")) +
      ggplot2::geom_line(ggplot2::aes_string(group = "GENE_NAME"), size = 2) + ggplot2::theme_bw() +
      ggplot2::geom_text(data = plot_lab, ggplot2::aes_string(x = "value", y = "y_value", label = "GENE_NAME"),
                hjust = -0.1,vjust = 0.3, size = 2.5) + ggplot2::xlim(start,end) +
      ggplot2::theme(axis.title.y = ggplot2::element_text(color = "white", size = 28),
            axis.text.y = ggplot2::element_blank(),
            axis.ticks.y = ggplot2::element_blank()) + ggplot2::xlab(paste0("Chromosome ", chr_in, " Position")) +
      ggplot2::ylim(0,(max(gene_sub$y_value)+1))

    if(len1 == len2){
      a = a + scale_y_reverse(labels = scaleFUN0)
      b = b + scale_y_continuous(labels = scaleFUN0)
    }else if(len1 > len2){
      a = a + scale_y_reverse(labels = scaleFUN1)
      diff = len1 - len2
      if(diff == 1){
        b = b + scale_y_continuous(labels = scaleFUN2)
      }else if(diff == 2){
        b = b + scale_y_continuous(labels = scaleFUN3)
      }else if(diff == 3){
        b = b + scale_y_continuous(labels = scaleFUN4)
      }
    }else if(len2 > len1){
      b = b + scale_y_continuous(labels = scaleFUN1)
      diff = len2 - len1
      if(diff == 1){
        a = a + scale_y_reverse(labels = scaleFUN2)
      }else if(diff == 2){
        a = a + scale_y_reverse(labels = scaleFUN3)
      }else if(diff == 3){
        a = a + scale_y_reverse(labels = scaleFUN4)
      }
    }

    if(label_lead == TRUE){
      a = a + geom_point(data = label_data_1, aes_string(x = "POS", y = "LOG10P"), color = "purple")
      a = a + geom_text(data = label_data_1, aes_string(label = "RS_ID"),
                        color = "black", size = 3, hjust = 1.25)

      b = b + geom_point(data = label_data_2, aes_string(x = "POS", y = "LOG10P"), color = "purple")
      b = b + geom_text(data = label_data_2, aes_string(label = "RS_ID"),
                        color = "black", size = 3, hjust = 1.25)
    }

    ggpubr::ggarrange(a, b, c, heights = c(2,2,1), nrow = 3, ncol = 1,
                      common.legend = TRUE, legend = "right")

}
oliviasabik/RACER documentation built on March 24, 2019, 8:36 p.m.