R/plotCorr.R

In roonysgalbi/tispec: Calculates tissue specificity from RNA-seq data

#' @name plotCorr
#' @title Plot correlation between expression and specificity
#' @description
#' This function plots quantile normalised expression values versus
#' tissue specificity values of all genes in all tissues to visualise 
#' correlation. 
#' @param x output from getTissue()
#' @param y optional vector of user defined genes for highlighting
#' @return
#' Returns a list object containing 3 objects: tauPlot, fracPlot, inputGeneSet. 
#' TauPlot is the result of plotting QN expression v the overall specificity of 
#' each gene for ANY tissue (tau). FracPlot is the result of plotting QN 
#' expression v the specificity of each gene for the tissue being plotted (tau 
#' expression fraction). InputGeneSet is the subset of rows from x containing 
#' only the genes listed by the user in y.
#' 
#' Yellow: tau expression fraction >= 0.85. 
#' 
#' Orange: tau expression fraction = 1.
#' 
#' Pink: user defined input gene set of interest 
#' 
#' Red: generalised additive model trend line
#' 
#' Swatch: 0.99 confidence interval
#'
#' r: correlation coefficient  
#' @examples
#' # Choose Input
#' corrPlots <- plotCorr(tissueA) # without user genes of interest
#' corrPlots <- plotCorr(tissueA, c('Col4a3', 'Mboat7')) # vector of genes
#' corrPlots <- plotCorr(tissueA, optimum$dataframe$external_gene_name) # output from getOptimum
#' 
#' # View results
#' #corrPlots$tauPlot
#' #corrPlots$fracPlot
#' #corrPlots$inputGeneSet
#' @import tidyverse
#' @export

plotCorr <- function(x,y){
    
    if(missing(y)){
        
        # WITHOUT USER PROVIDED GENE LIST:
        
        ## QN Exression v Tau
        asg <- x[x$frac == 1,]
        cor <- stats::cor.test(x$tau, x$qn, method = c("pearson"))
        corEst <-cor$estimate                  
        corEst <- paste("r = ",round(corEst, digits = 2),sep = "")
        tauPlot <- ggplot2::ggplot(x, ggplot2::aes_(x = quote(tau), y = quote(qn)))+
            ggplot2::geom_point(colour = '#56B4E9' , size = 1, alpha = 0.4)+
            ggplot2::geom_point(data = asg, colour = '#E69F00', size = 1.5, alpha = 0.8)+
            ggplot2::guides(fill = FALSE)+
            ggplot2::annotate("text", x = 0.95, y = 14, label = corEst, size = 6)+
            ggplot2::xlab('Specificity (tau)')+
            ggplot2::ylab('Expression')+
            ggplot2::scale_x_continuous(limits = c(0,1), breaks = round(seq(min(0), max(1), by = 0.2), 1))+
            ggplot2::scale_y_continuous(limits = c(0,14), breaks = round(seq(min(0), max(14), by = 2), 1))+
            ggplot2::stat_smooth(method = 'lm', level = 0.99, colour = "red", linetype = "dashed", size = 1, na.rm = TRUE)+
            ggplot2::theme_bw()+
            ggplot2::theme(
                plot.title = ggplot2::element_text(size = 20, face = "bold", hjust = 0.5),
                axis.title.x = ggplot2::element_text(size = 25, face = "bold"),
                axis.title.y = ggplot2::element_text(size = 25, face = "bold"),
                axis.text.x = ggplot2::element_text(size = 12, angle = 0, hjust = 0.5), 
                axis.text.y = ggplot2::element_text(size = 12),
                panel.border = ggplot2::element_rect(colour = "BLACK",size = 0.5),
                panel.grid.major = ggplot2::element_blank(),
                panel.grid.minor = ggplot2::element_blank(),
                strip.background = ggplot2::element_rect()
            )
        
        ## QN Expression v Tau Expression Fraction
        asg <- x[x$frac == 1,]
        hsg <- x[x$frac >= 0.85,]
        cor <- stats::cor.test(x$frac, x$qn, method = c("pearson"))
        corEst <-cor$estimate
        corEst <- paste("r = ",round(corEst, digits = 2),sep = "")
        fracPlot <- ggplot2::ggplot(x, ggplot2::aes_(x = quote(frac), y = quote(qn)))+
            ggplot2::geom_point(colour = '#56B4E9' , size = 1, alpha = 0.4)+
            ggplot2::geom_point(data = hsg, colour = '#F0E442', size = 1.5, alpha = 0.8)+
            ggplot2::geom_point(data = asg, colour = '#E69F00', size = 1.5, alpha = 0.8)+
            ggplot2::guides(fill = FALSE)+
            ggplot2::annotate("text", x = 0.95, y = 14, label = corEst, size = 6)+
            ggplot2::xlab('Specificity (frac)')+
            ggplot2::ylab('Expression')+
            ggplot2::scale_x_continuous(limits = c(0,1), breaks = round(seq(min(0), max(1), by = 0.2), 1))+
            ggplot2::scale_y_continuous(limits = c(0,14), breaks = round(seq(min(0), max(14), by = 2), 1))+
            ggplot2::stat_smooth(method = 'lm', level = 0.99, colour = "red", linetype = "dashed", size = 1, na.rm = TRUE)+
            ggplot2::theme_bw()+
            ggplot2::theme(
                plot.title = ggplot2::element_text(size = 20, face = "bold", hjust = 0.5),
                axis.title.x = ggplot2::element_text(size = 25, face = "bold"),
                axis.title.y = ggplot2::element_text(size = 25, face = "bold"),
                axis.text.x = ggplot2::element_text(size = 12, angle = 0, hjust = 0.5), 
                axis.text.y = ggplot2::element_text(size = 12),
                panel.border = ggplot2::element_rect(colour = "BLACK",size = 0.5),
                panel.grid.major = ggplot2::element_blank(),
                panel.grid.minor = ggplot2::element_blank(),
                strip.background = ggplot2::element_rect()
            )
        ## return a list of objects
        results <- list(tauPlot, fracPlot)
        names(results) <- c('tauPlot', 'fracPlot')
        return(results)
    } else {
        
        # WITH USER PROVIDED GENE LIST:
        
        ## parse gene list
        inputGeneSet <- x[x$external_gene_name %in% y,]
        inputGeneSet <- inputGeneSet[order(-inputGeneSet$score), ]
        
        ## QN Exression v Tau
        asg <- x[x$frac == 1,]
        cor <- stats::cor.test(x$tau, x$qn, method = c("pearson"))
        corEst <-cor$estimate                  
        corEst <- paste("r = ",round(corEst, digits = 2),sep = "")
        tauPlot <- ggplot2::ggplot(x, ggplot2::aes_(x = quote(tau), y = quote(qn)))+
            ggplot2::geom_point(colour = '#56B4E9' , size = 1, alpha = 0.4)+
            ggplot2::geom_point(data = asg, colour = '#E69F00', size = 1.5, alpha = 0.8)+
            ggplot2::geom_point(data = inputGeneSet, colour = '#CC79A7', size = 2.5, alpha = 0.8)+
            ggplot2::geom_text(data = inputGeneSet, label = inputGeneSet$external_gene_name, hjust=-0.2, vjust=-0.2, size=3, check_overlap = FALSE)+
            ggplot2::guides(fill = FALSE)+
            ggplot2::annotate("text", x = 0.95, y = 14, label = corEst, size = 6)+
            ggplot2::xlab('Specificity (tau)')+
            ggplot2::ylab('Expression')+
            ggplot2::scale_x_continuous(limits = c(0,1), breaks = round(seq(min(0), max(1), by = 0.2), 1))+
            ggplot2::scale_y_continuous(limits = c(0,14), breaks = round(seq(min(0), max(14), by = 2), 1))+
            ggplot2::stat_smooth(method = 'lm', level = 0.99, colour = "red", linetype = "dashed", size = 1, na.rm = TRUE)+
            ggplot2::theme_bw()+
            ggplot2::theme(
                plot.title = ggplot2::element_text(size = 20, face = "bold", hjust = 0.5),
                axis.title.x = ggplot2::element_text(size = 25, face = "bold"),
                axis.title.y = ggplot2::element_text(size = 25, face = "bold"),
                axis.text.x = ggplot2::element_text(size = 12, angle = 0, hjust = 0.5), 
                axis.text.y = ggplot2::element_text(size = 12),
                panel.border = ggplot2::element_rect(colour = "BLACK",size = 0.5),
                panel.grid.major = ggplot2::element_blank(),
                panel.grid.minor = ggplot2::element_blank(),
                strip.background = ggplot2::element_rect()
            )
        
        ## QN Expression v Tau Expression Fraction
        asg <- x[x$frac == 1,]
        hsg <- x[x$frac >= 0.85,]
        cor <- stats::cor.test(x$frac, x$qn, method = c("pearson"))
        corEst <-cor$estimate
        corEst <- paste("r = ",round(corEst, digits = 2),sep = "")
        fracPlot <- ggplot2::ggplot(x, ggplot2::aes_(x = quote(frac), y = quote(qn)))+
            ggplot2::geom_point(colour = '#56B4E9' , size = 1, alpha = 0.4)+
            ggplot2::geom_point(data = hsg, colour = '#F0E442', size = 1.5, alpha = 0.8)+
            ggplot2::geom_point(data = asg, colour = '#E69F00', size = 1.5, alpha = 0.8)+
            ggplot2::geom_point(data = inputGeneSet, colour = '#CC79A7', size = 2.5, alpha = 0.8)+
            ggplot2::geom_text(data = inputGeneSet, label = inputGeneSet$external_gene_name, hjust=-0.2, vjust=-0.2, size=3, check_overlap = FALSE)+
            ggplot2::guides(fill = FALSE)+
            ggplot2::annotate("text", x = 0.95, y = 14, label = corEst, size = 6)+
            ggplot2::xlab('Specificity (frac)')+
            ggplot2::ylab('Expression')+
            ggplot2::scale_x_continuous(limits = c(0,1), breaks = round(seq(min(0), max(1), by = 0.2), 1))+
            ggplot2::scale_y_continuous(limits = c(0,14), breaks = round(seq(min(0), max(14), by = 2), 1))+
            ggplot2::stat_smooth(method = 'lm', level = 0.99, colour = "red", linetype = "dashed", size = 1, na.rm = TRUE)+
            ggplot2::theme_bw()+
            ggplot2::theme(
                plot.title = ggplot2::element_text(size = 20, face = "bold", hjust = 0.5),
                axis.title.x = ggplot2::element_text(size = 25, face = "bold"),
                axis.title.y = ggplot2::element_text(size = 25, face = "bold"),
                axis.text.x = ggplot2::element_text(size = 12, angle = 0, hjust = 0.5), 
                axis.text.y = ggplot2::element_text(size = 12),
                panel.border = ggplot2::element_rect(colour = "BLACK",size = 0.5),
                panel.grid.major = ggplot2::element_blank(),
                panel.grid.minor = ggplot2::element_blank(),
                strip.background = ggplot2::element_rect()
            )
        ## return a list of objects
        results <- list(tauPlot, fracPlot, inputGeneSet)
        names(results) <- c('tauPlot', 'fracPlot', 'inputGeneSet')
        return(results)
    }
}