#' plotting of ranks obatined form diagnostic_matrix.RNAseq step
#' @description The function performs plotting of the evaluation data obtained at
#' the previous step 'diagnostic_matrix.RNAseq’.
#' @param diagnostic_matirx diagnostic_matirx obtained from the previous step `diagnostic_matrix.RNAseq`.
#' @examples diagnostic_plot.RNAseq(diagnostic_matirx)
#' @return A list of two plots-
#' (a) Output is `diagnostic_plot`, where the x-axis is the evaluation methods and the y-axis is the Rank of each normalization method.
#' (b) Additional plot to summarise rankings for each method as a violin plot including summary statistics for each BCM.
#' @name diagnostic_plot.RNAseq
#' @import GGally
#' @import Cairo
#' @importFrom dplyr dense_rank
#' @importFrom dplyr mutate_at
#' @importFrom tidyr pivot_longer
#' @importFrom ggpubr ggarrange
#' @importFrom colorspace divergingx_hcl
#' @importFrom hrbrthemes theme_ipsum
#' @export
diagnostic_plot.RNAseq <-function(diagnostic_matirx)
{
mycolors <- divergingx_hcl(9, palette = "Roma")
w3_m <- diagnostic_matirx$raw_rank
x11 <- as.data.frame((w3_m [1:6]))
row.names(x11) <- w3_m$method
x11 <- as.data.frame(t(x11[1:6]))
plot_df <- pivot_longer(x11, cols = 1:9)
diagnostic_plot <-
ggparcoord(data=w3_m, columns=1:6, groupColumn = "method",
scale = "globalminmax",
showPoints = TRUE,
alphaLines = 1,splineFactor=10
) + scale_y_reverse()+scale_color_manual(values=mycolors)+
theme_ipsum()+
xlab("Evaluation method") +
ylab( "Rank" ) +
theme(legend.position="top") + theme(text = element_text(family = "Times New Roman"))+
theme(axis.text.x = element_text(size=10, face="bold", color = "black"),
axis.text.y = element_text(size=10, face="bold", color = "black"),
legend.title=element_text(size=14, face="bold", color = "black"))
diagnostic_summary <- ggplot(plot_df, aes(x=name, y=value, fill=name)) + geom_violin(trim=TRUE, fill="gray")+
ylim(0,10) +
geom_boxplot(width=0.1)+ scale_color_manual(values=mycolors)+
theme_ipsum()+
xlab("Method") +
ylab( "Rank" ) +
theme(legend.position="top") + theme(text = element_text(family = "Times New Roman"))+
theme(axis.text.x = element_text(size=10, face="bold", color = "black", angle=90,hjust=1),
axis.text.y = element_text(size=10, face="bold", color = "black"),
legend.title=element_text(size=14, face="bold", color = "black"))
diagnostic_plot_list <<- list()
diagnostic_plot_list$diagnostic_plot <- diagnostic_plot
diagnostic_plot_list$diagnostic_stat_summary <- diagnostic_summary
diagnostic_plot_list
}
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