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#' @importFrom ggplot2 ggplot aes_string theme_bw xlab ylab ggtitle
#' geom_histogram theme element_text coord_cartesian geom_text geom_bar
#' scale_fill_manual
dm_plotDataFeatures <- function(tt, fill_color = "seagreen4"){
df <- data.frame(tt = tt)
ggp <- ggplot(df, aes_string(x = "tt")) +
theme_bw() +
xlab("Number of features per gene") +
ylab("Frequency") +
ggtitle(paste0(length(tt), " genes / ", sum(tt) , " features")) +
geom_histogram(fill = fill_color,
breaks = seq(min(df$tt), max(df$tt), by = 1)) +
theme(axis.text = element_text(size=16),
axis.title = element_text(size=18, face="bold"),
plot.title = element_text(size=18, face="bold")) +
coord_cartesian(xlim = c(0, max(tt) + 2))
return(ggp)
}
dm_plotDataBlocks <- function(tt, fill_color = "mediumpurple4"){
df <- data.frame(tt = tt)
binwidth <- ceiling(max(df$tt)/100)
ggp <- ggplot(df, aes_string(x = "tt")) +
theme_bw() +
xlab("Number of blocks per gene") +
ylab("Frequency") +
ggtitle(paste0(length(tt), " genes / ", sum(tt) , " blocks")) +
geom_histogram(fill = fill_color,
breaks = seq(min(df$tt), max(df$tt), by = binwidth)) +
theme(axis.text = element_text(size=16),
axis.title = element_text(size=18, face="bold"),
plot.title = element_text(size=18, face="bold")) +
coord_cartesian(xlim = c(0, max(tt) + 2))
return(ggp)
}
dm_plotDataSnps <- function(tt, fill_color = "royalblue4"){
df <- data.frame(tt = tt)
binwidth <- ceiling(max(df$tt)/100)
ggp <- ggplot(df, aes_string(x = "tt")) +
theme_bw() +
xlab("Number of SNPs per gene") +
ylab("Frequency") +
ggtitle(paste0(length(tt), " genes / ", sum(tt) , " SNPs")) +
geom_histogram(fill = fill_color,
breaks = seq(min(df$tt), max(df$tt), by = binwidth)) +
theme(axis.text = element_text(size=16),
axis.title = element_text(size=18, face="bold"),
plot.title = element_text(size=18, face="bold")) +
coord_cartesian(xlim = c(0, max(tt) + 2))
return(ggp)
}
#' Plot the frequency of present features
#'
#' @param info Data frame with \code{gene_id} and \code{feature_id} of ALL
#' features
#' @param ds_info Data frame with \code{gene_id} and \code{feature_id} of ONLY
#' DS features
#'
#' @return \code{ggplot} object
dm_plotDataDSInfo <- function(info, ds_info){
ds_info_spl <- split(as.character(ds_info$feature_id), factor(ds_info$gene_id))
info_spl <- split(as.character(info$feature_id), factor(info$gene_id))
genes <- names(info_spl)
tas <- table(unlist(lapply(names(ds_info_spl), function(g){
# g = "FBgn0004636"
if(! g %in% genes)
return(NA)
features_in <- sum(info_spl[[g]] %in% ds_info_spl[[g]])
return(features_in)
})), useNA = "always")
tas <- tas[c(length(tas), 1:(length(tas) -1))]
names(tas)[1] <- "NoGene"
df <- data.frame(x = factor(names(tas), levels = names(tas)),
y = as.numeric(tas), colors = "2", stringsAsFactors = FALSE)
df[df$x == "NoGene" | df$x == "0", "colors"] <- "1"
df$colors <- factor(df$colors)
ggp <- ggplot(data = df,
aes_string(x = "x", y = "y", label = "y", fill = "colors")) +
geom_bar(stat = "identity") +
geom_text(hjust = 0.5, vjust = 0, size = 6) +
theme_bw() +
xlab("Number of DS features left within DS gene") +
ylab("Number of DS genes") +
theme(axis.text = element_text(size=16),
axis.title = element_text(size=18, face="bold"),
plot.title = element_text(size=18, face="bold"),
legend.position = "none") +
scale_fill_manual(values = c("darkred", "grey"))
return(ggp)
}
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