R/createProfilePlot.R
In BIONF/PhyloProfile: PhyloProfile
Defines functions
addRankDivisionPlot
highlightProfilePlot
heatmapPlotting
dataCustomizedPlot
dataMainPlot
processOrthoID
Documented in
addRankDivisionPlot
dataCustomizedPlot
dataMainPlot
heatmapPlotting
highlightProfilePlot
processOrthoID
#' Process ortholog IDs
#' @description Process ortholog IDs to identify duplicated IDs
#' @param dataHeat a data frame contains processed profiles (see
#' ?fullProcessedProfile, ?filterProfileData)
#' @return the same dataframe as input, but the ortholog IDs are changed into
#' <taxID:orthoID>. New column {orthoFreq} specifies if the ortholog IDs are
#' single or duplicated
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @export
#' @examples
#' ?processOrthoID
#' \dontrun{
#' data("finalProcessedProfile", package="PhyloProfile")
#' processOrthoID(finalProcessedProfile)
#' }
processOrthoID <- function(dataHeat = NULL) {
if (is.null(dataHeat)) stop("Input data cannot be NULL!")
orthoID <- orthoFreqCount <- orthoFreqNew <- NULL
# predict if ortho ID in BIONF format
idFormat <- "other"
firstOrtho<-strsplit(as.character(dataHeat[1,]$orthoID),'|',fixed=TRUE)[[1]]
if (
length(firstOrtho) >= 3 && firstOrtho[1] == dataHeat[1,]$geneID &&
grepl(dataHeat[1,]$supertaxonID, firstOrtho[2])
) idFormat <- "bionf"
# parse orthoID
if (idFormat == "bionf") {
dataHeat <- within(
dataHeat,
orthoMod <- data.frame(
do.call('rbind', strsplit(as.character(orthoID),'|',fixed=TRUE))
)
)
dataHeat$orthoIDNew <- paste(
dataHeat$orthoMod$X2, dataHeat$orthoMod$X3, sep = "#"
)
} else {
dataHeat$orthoIDNew <- paste(
dataHeat$supertaxonID, dataHeat$orthoID, sep = "#"
)
}
dataHeat <- dataHeat[ , !(names(dataHeat) %in% ("orthoMod"))]
# count occurrences of ortho IDs
countOrthoDf <- as.data.frame(table(dataHeat$orthoIDNew))
colnames(countOrthoDf) <- c("orthoIDNew", "orthoFreq")
dataHeat <- merge(dataHeat, countOrthoDf, by = "orthoIDNew", all.x = TRUE)
dataHeat$orthoFreq[dataHeat$orthoFreq > 1] <- "Multiple"
dataHeat$orthoFreq[dataHeat$orthoFreq == 1] <- "Single"
# assign "Multiple" for pair seed - supertaxon if
# any of their co-orthologs are multiple
dt <- data.table(dataHeat[, c("geneID", "supertaxonID", "orthoFreq")])
dt <- dt[!duplicated(dt),]
dt[, orthoFreqCount := .N, by = c("geneID", "supertaxonID")]
dt$orthoFreq[dt$orthoFreqCount == 2] <- "Multiple"
dt <- dt[,c("geneID", "supertaxonID", "orthoFreq")][
!duplicated(dt[,c("geneID", "supertaxonID", "orthoFreq")]),
]
colnames(dt) <- c("geneID", "supertaxonID", "orthoFreqNew")
dataHeat <- merge(dataHeat, dt, by = c("geneID","supertaxonID"), all.x=TRUE)
dataHeat$orthoFreq <- dataHeat$orthoFreqNew
dataHeat <- subset(dataHeat, select = -c(orthoFreqNew))
return(dataHeat)
}
#' Create data for main profile plot
#' @export
#' @param dataHeat a data frame contains processed profiles (see
#' ?fullProcessedProfile, ?filterProfileData)
#' @return A dataframe for plotting the phylogenetic profile, containing seed
#' protein IDs (geneID), ortholog IDs (orthoID) together with their ncbi
#' taxonomy IDs (ncbiID and abbrName), full names (fullName), indexed supertaxa
#' (supertaxon), values for additional variables (var1, var2) and the aggregated
#' values of those additional variables for each supertaxon (mVar1, mVar2),
#' number of original and filtered co-orthologs in each supertaxon (paralog and
#' paralogNew), number of species in each supertaxon (numberSpec) and the % of
#' species that have orthologs in each supertaxon (presSpec).
#' @import data.table
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{filterProfileData}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' dataMainPlot(finalProcessedProfile)
dataMainPlot <- function(dataHeat = NULL){
if (is.null(dataHeat)) stop("Input data cannot be NULL!")
paralogNew <- orthoID <- NULL
# reduce number of inparalogs based on filtered dataHeat
dataHeatTb <- data.table(stats::na.omit(dataHeat))
dataHeatTb[, paralogNew := .N, by = c("geneID", "supertaxon")]
dataHeatTb <- data.frame(dataHeatTb[, c(
"geneID", "supertaxon", "paralogNew"
)])
dataHeat <- merge(
dataHeat, dataHeatTb, by = c("geneID", "supertaxon"), all.x = TRUE
)
dataHeat$paralog <- dataHeat$paralogNew
dataHeat <- dataHeat[!duplicated(dataHeat), ]
# remove unneeded dots
dataHeat$presSpec[dataHeat$presSpec == 0] <- NA
dataHeat$paralog[dataHeat$presSpec < 1] <- NA
dataHeat$paralog[dataHeat$paralog == 1] <- NA
# rescale numbers of paralogs
if (length(unique(stats::na.omit(dataHeat$paralog))) > 0) {
maxParalog <- max(stats::na.omit(dataHeat$paralog))
dataHeat$paralogSize <- (dataHeat$paralog / maxParalog) * 3
}
# remove prefix number of taxa names but keep the order
dataHeat$supertaxon <- factor(
substr(
as.character(dataHeat$supertaxon), 8 ,
nchar(as.character(dataHeat$supertaxon))),
levels = substr(
levels(as.factor(dataHeat$supertaxon)), 8,
nchar(levels(as.factor(dataHeat$supertaxon)))))
# count ortholog IDs for each taxon
dataHeat <- processOrthoID(dataHeat)
return(dataHeat)
}
#' Create data for customized profile plot
#' @description Create data for customized profile plot based on a selected
#' list of genes and/or taxa, containing seed protein IDs (geneID), ortholog IDs
#' (orthoID) together with their ncbi taxonomy IDs (ncbiID and abbrName), full
#' names (fullName), indexed supertaxa (supertaxon), values for additional
#' variables (var1, var2) and the aggregated values of those additional
#' variables for each supertaxon (mVar1, mVar2), number of original and filtered
#' co-orthologs in each supertaxon (paralog and paralogNew), number of species
#' in each supertaxon (numberSpec) and the % of species that have orthologs in
#' each supertaxon (presSpec).
#' @export
#' @usage dataCustomizedPlot(dataHeat = NULL, selectedTaxa = "all",
#' selectedSeq = "all")
#' @param dataHeat a data frame contains processed profiles (see
#' ?fullProcessedProfile, ?filterProfileData)
#' @param selectedTaxa selected subset of taxa. Default = "all".
#' @param selectedSeq selected subset of genes. Default = "all".
#' @return A dataframe contains data for plotting the customized profile.
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{filterProfileData}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' selectedTaxa <- c("Mammalia", "Saccharomycetes", "Insecta")
#' selectedSeq <- "all"
#' dataCustomizedPlot(finalProcessedProfile, selectedTaxa, selectedSeq)
dataCustomizedPlot <- function(
dataHeat = NULL, selectedTaxa = "all", selectedSeq = "all"
){
if (is.null(dataHeat)) stop("Input data cannot be NULL!")
geneID <- supertaxonMod <- paralogNew <- NULL
dataHeat$supertaxonMod <- {
substr(
dataHeat$supertaxon, 8, nchar(as.character(dataHeat$supertaxon))
)
}
if (selectedTaxa[1] == "all" & selectedSeq[1] != "all") {
dataHeat <- subset(dataHeat, geneID %in% selectedSeq)
} else if (selectedSeq[1] == "all" & selectedTaxa[1] != "all") {
dataHeat <- subset(dataHeat, supertaxonMod %in% selectedTaxa)
} else {
dataHeat <- subset(
dataHeat, geneID %in% selectedSeq & supertaxonMod %in% selectedTaxa
)
}
# reduce number of inparalogs based on filtered dataHeat
dataHeatTb <- data.table(stats::na.omit(dataHeat))
dataHeatTb[, paralogNew := .N, by = c("geneID", "supertaxon")]
dataHeatTb <- data.frame(
dataHeatTb[, c("geneID", "supertaxon", "paralogNew")]
)
dataHeat <- merge(
dataHeat, dataHeatTb, by = c("geneID", "supertaxon"), all.x = TRUE
)
dataHeat$paralog <- dataHeat$paralogNew
dataHeat <- dataHeat[!duplicated(dataHeat), ]
# remove unneeded dots
dataHeat$presSpec[dataHeat$presSpec == 0] <- NA
dataHeat$paralog[dataHeat$presSpec < 1] <- NA
dataHeat$paralog[dataHeat$paralog == 1] <- NA
# rescale numbers of paralogs
if (length(unique(stats::na.omit(dataHeat$paralog))) > 0) {
maxParalog <- max(stats::na.omit(dataHeat$paralog))
dataHeat$paralogSize <- (dataHeat$paralog / maxParalog) * 3
}
# remove prefix number of taxa names but keep the order
dataHeat$supertaxon <- factor(
substr(
as.character(dataHeat$supertaxon), 8,
nchar(as.character(dataHeat$supertaxon))),
levels = substr(
levels(dataHeat$supertaxon), 8,
nchar(levels(dataHeat$supertaxon))))
# count ortholog IDs for each taxon
if (nrow(dataHeat) == 0) return(dataHeat)
dataHeat <- processOrthoID(dataHeat)
return(dataHeat)
}
#' Create profile heatmap plot
#' @export
#' @param data dataframe for plotting the heatmap phylogentic profile (either
#' full or subset profiles)
#' @param parm plot parameters, including (1) type of x-axis "taxa" or
#' "genes" - default = "taxa"; (2+3) names of 2 variables var1ID and var2ID -
#' default = "var1" & "var2"; (4+5) mid value and color for mid value of var1 -
#' default is 0.5 and #FFFFFF; (6) color for lowest var1 - default = "#FF8C00";
#' (7) color for highest var1 - default = "#4682B4"; (8+9) mid value and color
#' for mid value of var2 - default is 1 and #FFFFFF;(10) color for lowest var2 -
#' default = "#FFFFFF", (11) color for highest var2 - default = "#F0E68C", (12)
#' color of co-orthologs - default = "#07D000"; (13+14+15) text sizes for x, y
#' axis and legend - default = 9 for each; (16) legend position "top", "bottom",
#' "right", "left" or "none" - default = "top"; (17) zoom ratio of the
#' co-ortholog dots from -1 to 3 - default = 0; (18) angle of x-axis from 0 to
#' 90 - default = 60; (19) show/hide separate line for reference taxon 1/0 -
#' default = 0; (20) enable/disable coloring gene categories TRUE/FALSE -
#' default = FALSE; (21) enable/disable coloring duplicated ortholog IDs
#' TRUE/FALSE - default=FALSE). NOTE: Leave blank or NULL to use default values.
#' @return A profile heatmap plot as a ggplot object.
#' @import ggplot2
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{dataMainPlot}}, \code{\link{dataCustomizedPlot}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' plotDf <- dataMainPlot(finalProcessedProfile)
#' plotParameter <- list(
#' "xAxis" = "taxa",
#' "var1ID" = "FAS_FW",
#' "var2ID" = "FAS_BW",
#' "midVar1" = 0.5,
#' "midColorVar1" = "#FFFFFF",
#' "lowColorVar1" = "#FF8C00",
#' "highColorVar1" = "#4682B4",
#' "midVar2" = 1,
#' "midColorVar2" = "#FFFFFF",
#' "lowColorVar2" = "#CB4C4E",
#' "highColorVar2" = "#3E436F",
#' "paraColor" = "#07D000",
#' "xSize" = 8,
#' "ySize" = 8,
#' "legendSize" = 8,
#' "mainLegend" = "top",
#' "dotZoom" = 0,
#' "xAngle" = 60,
#' "guideline" = 0,
#' "colorByGroup" = FALSE,
#' "catColors" = NULL,
#' "colorByOrthoID" = FALSE
#' )
#'
#' heatmapPlotting(plotDf, plotParameter)
heatmapPlotting <- function(data = NULL, parm = NULL){
if (is.null(data)) stop("Input data cannot be NULL!")
if (is.null(parm))
parm <- list(
"xAxis" = "taxa", "var1ID" = "var1", "var2ID" = "var2",
"midVar1" = 0.5, "midColorVar1" = "#FFFFFF",
"lowColorVar1" = "#FF8C00", "highColorVar1" = "#4682B4",
"midVar2" = 1, "midColorVar2" = "#FFFFFF",
"lowColorVar2" = "#CB4C4E", "highColorVar2" = "#3E436F",
"paraColor" = "#07D000", "xSize" = 8, "ySize" = 8, "legendSize" = 8,
"mainLegend" = "top", "dotZoom" = 0, "xAngle" = 60, "guideline" = 0,
"colorByGroup" = FALSE,"catColors" = NULL,"colorByOrthoID" = FALSE)
geneID <- supertaxon <- category <-var1<-var2 <- presSpec <- paralog <- NULL
orthoFreq <- xmin <- xmax <- ymin <- ymax <- NULL
### create heatmap plot
# create geom_tile & scale_fill_gradient for var2 OR gene category
if (parm$xAxis == "genes") p <- ggplot(data,aes(x = geneID, y = supertaxon))
else p <- ggplot(data, aes(y = geneID, x = supertaxon))
if (parm$colorByGroup == TRUE) {
p <- p + geom_tile(aes(fill = factor(category)), alpha = 0.3)
if (!is.null(parm$catColors))
p <- p + scale_fill_manual(values = parm$catColors)
} else {
if (length(unique(stats::na.omit(data$var2))) != 1)
p <- p + scale_fill_gradient2(
low = parm$lowColorVar2, high = parm$highColorVar2,
mid = parm$midColorVar2, midpoint = parm$midVar2,
na.value = "gray95", limits = c(0, 1)) +
geom_tile(aes(fill = var2))
}
# create geom_point for found ortho; coloring by var1 or
# orthoIDs (only when working on lowest taxonomy rank)
# and inparalogs (co-orthologs)
if (length(unique(stats::na.omit(data$presSpec))) < 2) {
# working on the lowest taxonomy rank
if (parm$colorByOrthoID == TRUE) {
# color by ortho IDs
p <- p + geom_point(
aes(colour = factor(orthoFreq)), na.rm = TRUE,
size = data$presSpec*5*(1+parm$dotZoom), show.legend = TRUE
)
} else {
if (length(unique(stats::na.omit(data$var1))) == 1) {
p <- p + geom_point(
aes(colour = var1), na.rm = TRUE,
size = data$presSpec*5*(1+parm$dotZoom), show.legend = FALSE
)
} else {
p <- p +
geom_point(
aes(colour = var1), na.rm = TRUE,
size = data$presSpec * 5 * (1 + parm$dotZoom)) +
scale_color_gradient2(
low = parm$lowColorVar1, high = parm$highColorVar1,
mid = parm$midColorVar1, midpoint = parm$midVar1,
limits = c(0,1)
)
}
# plot inparalogs (if available)
if (length(unique(stats::na.omit(data$paralog))) > 0) {
p <- p +
geom_point(
data = data, aes(size = paralog), color=parm$paraColor,
na.rm = TRUE, show.legend = TRUE) +
guides(size = guide_legend(title = "# of co-orthologs")) +
scale_size_continuous(range = c(
min(stats::na.omit(data$paralogSize))*(1+parm$dotZoom),
max(stats::na.omit(data$paralogSize))*(1+parm$dotZoom)))
}
}
} else {
# scale dot size based on % preSpec in each super taxon
if (length(unique(stats::na.omit(data$var1))) == 1) {
p <- p + geom_point(aes(size=presSpec),color="#336a98",na.rm = TRUE)
} else {
p <- p + geom_point(aes(colour=var1, size = presSpec),na.rm = TRUE)+
scale_color_gradient2(
low = parm$lowColorVar1, high = parm$highColorVar1,
mid = parm$midColorVar1, midpoint = parm$midVar1,
limits = c(0,1)
)
}
# remain the scale of point while filtering % presSpec
presentVl <- data$presSpec[!is.na(data$presSpec)]
p <- p + scale_size_continuous(range = c(
(floor(min(presentVl) * 10) / 10 * 5) * (1 + parm$dotZoom),
(floor(max(presentVl) * 10) / 10 * 5) * (1 + parm$dotZoom)))
}
# create legend
if (parm$colorByGroup == FALSE) {
if (parm$colorByOrthoID == FALSE) {
p <- p + guides(fill = guide_colourbar(title = parm$var2ID),
color = guide_colourbar(title = parm$var1ID))
} else {
p <- p + guides(fill = guide_colourbar(title = parm$var2ID),
color = guide_legend(title = 'OrthoID copy number'))
}
} else {
p <- p + guides(fill = guide_legend("Category"),
color = guide_colourbar(title = parm$var1ID))
}
# guideline for separating ref species
if (parm$guideline == 1) {
if (parm$xAxis == "genes") {
p <- p + labs(y = "Taxon") +
geom_hline(yintercept = 0.5, colour = "dodgerblue4") +
geom_hline(yintercept = 1.5, colour = "dodgerblue4")
} else
p <- p + labs(x = "Taxon") +
geom_vline(xintercept = 0.5, colour = "dodgerblue4") +
geom_vline(xintercept = 1.5, colour = "dodgerblue4")
}
# text size, legend position
p <- p + theme_minimal(base_size = 9)
vjustValue <- 1
if (parm$xAngle == 90) vjustValue <- 0.5
p <- p + theme(
axis.text.x = element_text(
angle = parm$xAngle, hjust = 1, size = parm$xSize,
vjust = vjustValue
),
axis.text.y = element_text(size = parm$ySize),
axis.title.x = element_text(size = parm$xSize),
axis.title.y = element_text(size = parm$ySize),
legend.title = element_text(size = parm$legendSize),
legend.text = element_text(size = parm$legendSize),
legend.position = parm$mainLegend)
return(p)
}
#' Highlight gene and/or taxon of interest on the phylogenetic profile plot
#' @export
#' @usage highlightProfilePlot(profilePlot = NULL, plotDf = NULL,
#' taxonHighlight = "none", workingRank = "none", geneHighlight = NULL,
#' taxDB = NULL, xAxis = "taxa")
#' @param profilePlot initial (highlighted) profile plot
#' @param plotDf dataframe for plotting the heatmap phylogentic profile
#' @param taxonHighlight taxon of interst. Default = "none".
#' @param workingRank working taxonomy rank (needed only for highlight taxon).
#' @param geneHighlight gene of interest. Default = NULL.
#' @param taxDB Path to the taxonomy DB files
#' @param xAxis type of x-axis (either "genes" or "taxa")
#' @return A profile heatmap plot with highlighted gene and/or taxon of interest
#' as ggplot object.
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{dataMainPlot}}, \code{\link{dataCustomizedPlot}},
#' \code{\link{heatmapPlotting}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' plotDf <- dataMainPlot(finalProcessedProfile)
#' plotParameter <- list(
#' "xAxis" = "taxa",
#' "var1ID" = "FAS_FW",
#' "var2ID" = "FAS_BW",
#' "midVar1" = 0.5,
#' "midColorVar1" = "#FFFFFF",
#' "lowColorVar1" = "#FF8C00",
#' "highColorVar1" = "#4682B4",
#' "midVar2" = 1,
#' "midColorVar2" = "#FFFFFF",
#' "lowColorVar2" = "#CB4C4E",
#' "highColorVar2" = "#3E436F",
#' "paraColor" = "#07D000",
#' "xSize" = 8,
#' "ySize" = 8,
#' "legendSize" = 8,
#' "mainLegend" = "top",
#' "dotZoom" = 0,
#' "xAngle" = 60,
#' "guideline" = 0,
#' "colorByGroup" = FALSE,
#' "colorByOrthoID" = FALSE
#' )
#' profilePlot <- heatmapPlotting(plotDf, plotParameter)
#' taxonHighlight <- "none"
#' workingRank <- "class"
#' geneHighlight <- "100265at6656"
#' highlightProfilePlot(
#' profilePlot, plotDf, taxonHighlight, workingRank, geneHighlight,
#' NULL, plotParameter$xAxis
#' )
highlightProfilePlot <- function(
profilePlot = NULL, plotDf = NULL, taxonHighlight = "none",
workingRank = "none", geneHighlight = NULL, taxDB = NULL, xAxis = "taxa"
){
if (is.null(plotDf)) stop("Input data cannot be NULL!")
if (is.null(profilePlot)) stop("Profile plot cannot be NULL!")
xmin <- xmax <- ymin <- ymax <- NULL
if (is.null(taxonHighlight) && is.null(geneHighlight)) return(profilePlot)
# highlight taxon
if (length(taxonHighlight) > 0 && !("none" %in% taxonHighlight)) {
# get selected highlight taxon ID
taxName <- getNameList(taxDB)
taxonHighlightID <- taxName$ncbiID[
taxName$fullName %in% taxonHighlight & taxName$rank == workingRank]
if (length(taxonHighlightID) == 0L) {
taxonHighlightID <- taxName$ncbiID[
taxName$fullName %in% taxonHighlight
]
} else if(length(taxonHighlightID) < length(taxonHighlight)) {
missingID <- taxName$ncbiID[
taxName$fullName %in% taxonHighlight
]
missingID <- missingID[!(missingID %in% taxonHighlightID)]
taxonHighlightID <- c(taxonHighlightID, missingID)
}
# get taxonID together with it sorted index
selTaxon <- unique(as.character(
plotDf$supertaxon[plotDf$supertaxonID %in% taxonHighlightID]
))
selIndex <- match(selTaxon, levels(as.factor(plotDf$supertaxon)))
if (xAxis == "taxa") {
rect <- data.frame(
xmin=selIndex-0.5, xmax = selIndex+0.5, ymin = -Inf, ymax = Inf)
} else
rect <- data.frame(
ymin=selIndex-0.5, ymax = selIndex+0.5, xmin = -Inf, xmax = Inf)
profilePlot <- profilePlot + geom_rect(
data = rect, color = "yellow", alpha = 0.3, inherit.aes = FALSE,
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax))
}
# highlight gene
if (length(geneHighlight) > 0 && !("none" %in% geneHighlight)) {
selIndex <- match(geneHighlight, levels(as.factor(plotDf$geneID)))
if (xAxis == "taxa") {
rect <- data.frame(
ymin=selIndex-0.5, ymax = selIndex+0.5, xmin = -Inf, xmax = Inf)
} else
rect <- data.frame(
xmin=selIndex-0.5, xmax = selIndex+0.5, ymin = -Inf, ymax = Inf)
profilePlot <- profilePlot + geom_rect(
data = rect, color = "yellow", alpha = 0.3, inherit.aes = FALSE,
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax))
}
return(profilePlot)
}
#' Add taxonomy rank division lines to the heatmap plot
#' @export
#' @usage addRankDivisionPlot(profilePlot = NULL, plotDf = NULL,
#' taxDB = NULL, workingRank = NULL, superRank = NULL, xAxis = "taxa",
#' groupLabelSize = 14, groupLabelDist = 2, groupLabelAngle = 90)
#' @param profilePlot initial (highlighted) profile plot
#' @param plotDf dataframe for plotting the heatmap phylogentic profile
#' @param taxDB path to taxonomy database (taxonomyMatrix.txt file required!)
#' @param workingRank working taxonomy rank (e.g. species)
#' @param superRank taxonomy rank for division lines (e.g. superkingdom)
#' @param xAxis type of x-axis (either "genes" or "taxa")
#' @param groupLabelSize size of rank labels
#' @param groupLabelDist size of the plot area for rank labels
#' @param groupLabelAngle angle of rank labels
#' @return A profile heatmap plot with highlighted gene and/or taxon of interest
#' as ggplot object.
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{heatmapPlotting}}, \code{\link{highlightProfilePlot}},
#' \code{\link{getTaxonomyMatrix}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' plotDf <- dataMainPlot(finalProcessedProfile)
#' plotParameter <- list(
#' "xAxis" = "taxa",
#' "var1ID" = "FAS_FW",
#' "var2ID" = "FAS_BW",
#' "midVar1" = 0.5,
#' "midColorVar1" = "#FFFFFF",
#' "lowColorVar1" = "#FF8C00",
#' "highColorVar1" = "#4682B4",
#' "midVar2" = 1,
#' "midColorVar2" = "#FFFFFF",
#' "lowColorVar2" = "#CB4C4E",
#' "highColorVar2" = "#3E436F",
#' "paraColor" = "#07D000",
#' "xSize" = 8,
#' "ySize" = 8,
#' "legendSize" = 8,
#' "mainLegend" = "top",
#' "dotZoom" = 0,
#' "xAngle" = 60,
#' "guideline" = 0,
#' "colorByGroup" = FALSE,
#' "colorByOrthoID" = FALSE
#' )
#' profilePlot <- heatmapPlotting(plotDf, plotParameter)
#' workingRank <- "class"
#' superRank <- "superkingdom"
#' addRankDivisionPlot(
#' profilePlot, plotDf, NULL, workingRank, superRank, "taxa"
#' )
addRankDivisionPlot <- function(
profilePlot = NULL, plotDf = NULL, taxDB = NULL,
workingRank = NULL, superRank = NULL, xAxis = "taxa",
groupLabelSize = 14, groupLabelDist = 2, groupLabelAngle = 90
) {
if (is.null(plotDf)) stop("Input data cannot be NULL!")
if (is.null(profilePlot)) stop("Profile plot cannot be NULL!")
if (is.null(workingRank) || is.null(superRank)) {
# guideline for separating ref species
if (xAxis == "genes") {
profilePlot <- profilePlot + labs(y = "Taxon") +
geom_hline(yintercept = 0.5, colour = "dodgerblue4") +
geom_hline(yintercept = 1.5, colour = "dodgerblue4")
} else
profilePlot <- profilePlot + labs(x = "Taxon") +
geom_vline(xintercept = 0.5, colour = "dodgerblue4") +
geom_vline(xintercept = 1.5, colour = "dodgerblue4")
return(profilePlot)
} else {
# sort supertaxonID based on the sorted supertaxon
plotDf <- plotDf[with(plotDf,order(supertaxon)),]
plotDf$supertaxonID <- factor(
plotDf$supertaxonID, levels = unique(plotDf$supertaxonID)
)
# get input (super)taxa
inputTax <- levels(as.factor(plotDf$supertaxonID))
# subset taxonomy matrix to contain only superrank for division line
taxMatrix <- getTaxonomyMatrix(taxDB)
subTaxMatrix <- subset(
taxMatrix[taxMatrix[[workingRank]] %in% inputTax,],
select = c(as.character(workingRank), as.character(superRank))
)
subTaxMatrix <- subTaxMatrix[!duplicated(subTaxMatrix),]
# remove IDs that do not have real NCBI superRank
nameList <- getNameList(taxDB)
subNameList <- nameList[
nameList$ncbiID %in% subTaxMatrix[[superRank]],
c("ncbiID", "rank", "fullName")
]
colnames(subNameList) <- c(superRank, "rank", "name")
mergedDf <- merge(subTaxMatrix, subNameList, by = superRank, all.x=TRUE)
mergedDf <- mergedDf[mergedDf$rank == superRank,]
subTaxMatrix <- mergedDf
# group input taxa based on superrank and get their index
groupedList <- lapply(
levels(as.factor(subTaxMatrix[[superRank]])),
function(x) {
tmp <- subTaxMatrix[subTaxMatrix[[superRank]] == x,]
tmp$index <- which(
levels(as.factor(plotDf$supertaxonID))
%in% tmp[[workingRank]]
)
return(tmp)
}
)
# add vertical line to divide taxon groups
# add vertical line to divide taxon groups
max_taxa <- length(unique(as.character(plotDf$geneID)))
for(i in groupedList) {
min <- min(i$index)
max <- max(i$index)
if (xAxis == "taxa") {
profilePlot <- profilePlot +
geom_vline(xintercept = min - 0.5, colour = "dodgerblue4") +
geom_vline(xintercept = max + 0.5, colour = "dodgerblue4") +
annotate(
geom = "text", angle = groupLabelAngle, hjust = 0,
size = groupLabelSize,
x = min,
y = max_taxa + 0.5,
label = unique(as.character(i$name))
)
} else {
profilePlot <- profilePlot +
geom_hline(yintercept = min - 0.5, colour = "dodgerblue4") +
geom_hline(yintercept = max + 0.5, colour = "dodgerblue4") +
annotate(
geom = "text", angle = groupLabelAngle - 90, hjust = 0,
size = groupLabelSize,
y = min,
x = max_taxa + 1,
label = unique(as.character(i$name))
)
}
}
if (xAxis == "taxa") {
return(
profilePlot + coord_cartesian(
clip = 'off', ylim = c(1, max_taxa + groupLabelDist)
)
)
} else
return(
profilePlot + coord_cartesian(
clip = 'off', xlim = c(1, max_taxa + groupLabelDist)
)
)
}
}
BIONF/PhyloProfile documentation built on April 14, 2024, 10:39 p.m.
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Defines functions addRankDivisionPlot highlightProfilePlot heatmapPlotting dataCustomizedPlot dataMainPlot processOrthoID
Documented in addRankDivisionPlot dataCustomizedPlot dataMainPlot heatmapPlotting highlightProfilePlot processOrthoID
#' Process ortholog IDs
#' @description Process ortholog IDs to identify duplicated IDs
#' @param dataHeat a data frame contains processed profiles (see
#' ?fullProcessedProfile, ?filterProfileData)
#' @return the same dataframe as input, but the ortholog IDs are changed into
#' <taxID:orthoID>. New column {orthoFreq} specifies if the ortholog IDs are
#' single or duplicated
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @export
#' @examples
#' ?processOrthoID
#' \dontrun{
#' data("finalProcessedProfile", package="PhyloProfile")
#' processOrthoID(finalProcessedProfile)
#' }
processOrthoID <- function(dataHeat = NULL) {
if (is.null(dataHeat)) stop("Input data cannot be NULL!")
orthoID <- orthoFreqCount <- orthoFreqNew <- NULL
# predict if ortho ID in BIONF format
idFormat <- "other"
firstOrtho<-strsplit(as.character(dataHeat[1,]$orthoID),'|',fixed=TRUE)[[1]]
if (
length(firstOrtho) >= 3 && firstOrtho[1] == dataHeat[1,]$geneID &&
grepl(dataHeat[1,]$supertaxonID, firstOrtho[2])
) idFormat <- "bionf"
# parse orthoID
if (idFormat == "bionf") {
dataHeat <- within(
dataHeat,
orthoMod <- data.frame(
do.call('rbind', strsplit(as.character(orthoID),'|',fixed=TRUE))
)
)
dataHeat$orthoIDNew <- paste(
dataHeat$orthoMod$X2, dataHeat$orthoMod$X3, sep = "#"
)
} else {
dataHeat$orthoIDNew <- paste(
dataHeat$supertaxonID, dataHeat$orthoID, sep = "#"
)
}
dataHeat <- dataHeat[ , !(names(dataHeat) %in% ("orthoMod"))]
# count occurrences of ortho IDs
countOrthoDf <- as.data.frame(table(dataHeat$orthoIDNew))
colnames(countOrthoDf) <- c("orthoIDNew", "orthoFreq")
dataHeat <- merge(dataHeat, countOrthoDf, by = "orthoIDNew", all.x = TRUE)
dataHeat$orthoFreq[dataHeat$orthoFreq > 1] <- "Multiple"
dataHeat$orthoFreq[dataHeat$orthoFreq == 1] <- "Single"
# assign "Multiple" for pair seed - supertaxon if
# any of their co-orthologs are multiple
dt <- data.table(dataHeat[, c("geneID", "supertaxonID", "orthoFreq")])
dt <- dt[!duplicated(dt),]
dt[, orthoFreqCount := .N, by = c("geneID", "supertaxonID")]
dt$orthoFreq[dt$orthoFreqCount == 2] <- "Multiple"
dt <- dt[,c("geneID", "supertaxonID", "orthoFreq")][
!duplicated(dt[,c("geneID", "supertaxonID", "orthoFreq")]),
]
colnames(dt) <- c("geneID", "supertaxonID", "orthoFreqNew")
dataHeat <- merge(dataHeat, dt, by = c("geneID","supertaxonID"), all.x=TRUE)
dataHeat$orthoFreq <- dataHeat$orthoFreqNew
dataHeat <- subset(dataHeat, select = -c(orthoFreqNew))
return(dataHeat)
}
#' Create data for main profile plot
#' @export
#' @param dataHeat a data frame contains processed profiles (see
#' ?fullProcessedProfile, ?filterProfileData)
#' @return A dataframe for plotting the phylogenetic profile, containing seed
#' protein IDs (geneID), ortholog IDs (orthoID) together with their ncbi
#' taxonomy IDs (ncbiID and abbrName), full names (fullName), indexed supertaxa
#' (supertaxon), values for additional variables (var1, var2) and the aggregated
#' values of those additional variables for each supertaxon (mVar1, mVar2),
#' number of original and filtered co-orthologs in each supertaxon (paralog and
#' paralogNew), number of species in each supertaxon (numberSpec) and the % of
#' species that have orthologs in each supertaxon (presSpec).
#' @import data.table
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{filterProfileData}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' dataMainPlot(finalProcessedProfile)
dataMainPlot <- function(dataHeat = NULL){
if (is.null(dataHeat)) stop("Input data cannot be NULL!")
paralogNew <- orthoID <- NULL
# reduce number of inparalogs based on filtered dataHeat
dataHeatTb <- data.table(stats::na.omit(dataHeat))
dataHeatTb[, paralogNew := .N, by = c("geneID", "supertaxon")]
dataHeatTb <- data.frame(dataHeatTb[, c(
"geneID", "supertaxon", "paralogNew"
)])
dataHeat <- merge(
dataHeat, dataHeatTb, by = c("geneID", "supertaxon"), all.x = TRUE
)
dataHeat$paralog <- dataHeat$paralogNew
dataHeat <- dataHeat[!duplicated(dataHeat), ]
# remove unneeded dots
dataHeat$presSpec[dataHeat$presSpec == 0] <- NA
dataHeat$paralog[dataHeat$presSpec < 1] <- NA
dataHeat$paralog[dataHeat$paralog == 1] <- NA
# rescale numbers of paralogs
if (length(unique(stats::na.omit(dataHeat$paralog))) > 0) {
maxParalog <- max(stats::na.omit(dataHeat$paralog))
dataHeat$paralogSize <- (dataHeat$paralog / maxParalog) * 3
}
# remove prefix number of taxa names but keep the order
dataHeat$supertaxon <- factor(
substr(
as.character(dataHeat$supertaxon), 8 ,
nchar(as.character(dataHeat$supertaxon))),
levels = substr(
levels(as.factor(dataHeat$supertaxon)), 8,
nchar(levels(as.factor(dataHeat$supertaxon)))))
# count ortholog IDs for each taxon
dataHeat <- processOrthoID(dataHeat)
return(dataHeat)
}
#' Create data for customized profile plot
#' @description Create data for customized profile plot based on a selected
#' list of genes and/or taxa, containing seed protein IDs (geneID), ortholog IDs
#' (orthoID) together with their ncbi taxonomy IDs (ncbiID and abbrName), full
#' names (fullName), indexed supertaxa (supertaxon), values for additional
#' variables (var1, var2) and the aggregated values of those additional
#' variables for each supertaxon (mVar1, mVar2), number of original and filtered
#' co-orthologs in each supertaxon (paralog and paralogNew), number of species
#' in each supertaxon (numberSpec) and the % of species that have orthologs in
#' each supertaxon (presSpec).
#' @export
#' @usage dataCustomizedPlot(dataHeat = NULL, selectedTaxa = "all",
#' selectedSeq = "all")
#' @param dataHeat a data frame contains processed profiles (see
#' ?fullProcessedProfile, ?filterProfileData)
#' @param selectedTaxa selected subset of taxa. Default = "all".
#' @param selectedSeq selected subset of genes. Default = "all".
#' @return A dataframe contains data for plotting the customized profile.
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{filterProfileData}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' selectedTaxa <- c("Mammalia", "Saccharomycetes", "Insecta")
#' selectedSeq <- "all"
#' dataCustomizedPlot(finalProcessedProfile, selectedTaxa, selectedSeq)
dataCustomizedPlot <- function(
dataHeat = NULL, selectedTaxa = "all", selectedSeq = "all"
){
if (is.null(dataHeat)) stop("Input data cannot be NULL!")
geneID <- supertaxonMod <- paralogNew <- NULL
dataHeat$supertaxonMod <- {
substr(
dataHeat$supertaxon, 8, nchar(as.character(dataHeat$supertaxon))
)
}
if (selectedTaxa[1] == "all" & selectedSeq[1] != "all") {
dataHeat <- subset(dataHeat, geneID %in% selectedSeq)
} else if (selectedSeq[1] == "all" & selectedTaxa[1] != "all") {
dataHeat <- subset(dataHeat, supertaxonMod %in% selectedTaxa)
} else {
dataHeat <- subset(
dataHeat, geneID %in% selectedSeq & supertaxonMod %in% selectedTaxa
)
}
# reduce number of inparalogs based on filtered dataHeat
dataHeatTb <- data.table(stats::na.omit(dataHeat))
dataHeatTb[, paralogNew := .N, by = c("geneID", "supertaxon")]
dataHeatTb <- data.frame(
dataHeatTb[, c("geneID", "supertaxon", "paralogNew")]
)
dataHeat <- merge(
dataHeat, dataHeatTb, by = c("geneID", "supertaxon"), all.x = TRUE
)
dataHeat$paralog <- dataHeat$paralogNew
dataHeat <- dataHeat[!duplicated(dataHeat), ]
# remove unneeded dots
dataHeat$presSpec[dataHeat$presSpec == 0] <- NA
dataHeat$paralog[dataHeat$presSpec < 1] <- NA
dataHeat$paralog[dataHeat$paralog == 1] <- NA
# rescale numbers of paralogs
if (length(unique(stats::na.omit(dataHeat$paralog))) > 0) {
maxParalog <- max(stats::na.omit(dataHeat$paralog))
dataHeat$paralogSize <- (dataHeat$paralog / maxParalog) * 3
}
# remove prefix number of taxa names but keep the order
dataHeat$supertaxon <- factor(
substr(
as.character(dataHeat$supertaxon), 8,
nchar(as.character(dataHeat$supertaxon))),
levels = substr(
levels(dataHeat$supertaxon), 8,
nchar(levels(dataHeat$supertaxon))))
# count ortholog IDs for each taxon
if (nrow(dataHeat) == 0) return(dataHeat)
dataHeat <- processOrthoID(dataHeat)
return(dataHeat)
}
#' Create profile heatmap plot
#' @export
#' @param data dataframe for plotting the heatmap phylogentic profile (either
#' full or subset profiles)
#' @param parm plot parameters, including (1) type of x-axis "taxa" or
#' "genes" - default = "taxa"; (2+3) names of 2 variables var1ID and var2ID -
#' default = "var1" & "var2"; (4+5) mid value and color for mid value of var1 -
#' default is 0.5 and #FFFFFF; (6) color for lowest var1 - default = "#FF8C00";
#' (7) color for highest var1 - default = "#4682B4"; (8+9) mid value and color
#' for mid value of var2 - default is 1 and #FFFFFF;(10) color for lowest var2 -
#' default = "#FFFFFF", (11) color for highest var2 - default = "#F0E68C", (12)
#' color of co-orthologs - default = "#07D000"; (13+14+15) text sizes for x, y
#' axis and legend - default = 9 for each; (16) legend position "top", "bottom",
#' "right", "left" or "none" - default = "top"; (17) zoom ratio of the
#' co-ortholog dots from -1 to 3 - default = 0; (18) angle of x-axis from 0 to
#' 90 - default = 60; (19) show/hide separate line for reference taxon 1/0 -
#' default = 0; (20) enable/disable coloring gene categories TRUE/FALSE -
#' default = FALSE; (21) enable/disable coloring duplicated ortholog IDs
#' TRUE/FALSE - default=FALSE). NOTE: Leave blank or NULL to use default values.
#' @return A profile heatmap plot as a ggplot object.
#' @import ggplot2
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{dataMainPlot}}, \code{\link{dataCustomizedPlot}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' plotDf <- dataMainPlot(finalProcessedProfile)
#' plotParameter <- list(
#' "xAxis" = "taxa",
#' "var1ID" = "FAS_FW",
#' "var2ID" = "FAS_BW",
#' "midVar1" = 0.5,
#' "midColorVar1" = "#FFFFFF",
#' "lowColorVar1" = "#FF8C00",
#' "highColorVar1" = "#4682B4",
#' "midVar2" = 1,
#' "midColorVar2" = "#FFFFFF",
#' "lowColorVar2" = "#CB4C4E",
#' "highColorVar2" = "#3E436F",
#' "paraColor" = "#07D000",
#' "xSize" = 8,
#' "ySize" = 8,
#' "legendSize" = 8,
#' "mainLegend" = "top",
#' "dotZoom" = 0,
#' "xAngle" = 60,
#' "guideline" = 0,
#' "colorByGroup" = FALSE,
#' "catColors" = NULL,
#' "colorByOrthoID" = FALSE
#' )
#'
#' heatmapPlotting(plotDf, plotParameter)
heatmapPlotting <- function(data = NULL, parm = NULL){
if (is.null(data)) stop("Input data cannot be NULL!")
if (is.null(parm))
parm <- list(
"xAxis" = "taxa", "var1ID" = "var1", "var2ID" = "var2",
"midVar1" = 0.5, "midColorVar1" = "#FFFFFF",
"lowColorVar1" = "#FF8C00", "highColorVar1" = "#4682B4",
"midVar2" = 1, "midColorVar2" = "#FFFFFF",
"lowColorVar2" = "#CB4C4E", "highColorVar2" = "#3E436F",
"paraColor" = "#07D000", "xSize" = 8, "ySize" = 8, "legendSize" = 8,
"mainLegend" = "top", "dotZoom" = 0, "xAngle" = 60, "guideline" = 0,
"colorByGroup" = FALSE,"catColors" = NULL,"colorByOrthoID" = FALSE)
geneID <- supertaxon <- category <-var1<-var2 <- presSpec <- paralog <- NULL
orthoFreq <- xmin <- xmax <- ymin <- ymax <- NULL
### create heatmap plot
# create geom_tile & scale_fill_gradient for var2 OR gene category
if (parm$xAxis == "genes") p <- ggplot(data,aes(x = geneID, y = supertaxon))
else p <- ggplot(data, aes(y = geneID, x = supertaxon))
if (parm$colorByGroup == TRUE) {
p <- p + geom_tile(aes(fill = factor(category)), alpha = 0.3)
if (!is.null(parm$catColors))
p <- p + scale_fill_manual(values = parm$catColors)
} else {
if (length(unique(stats::na.omit(data$var2))) != 1)
p <- p + scale_fill_gradient2(
low = parm$lowColorVar2, high = parm$highColorVar2,
mid = parm$midColorVar2, midpoint = parm$midVar2,
na.value = "gray95", limits = c(0, 1)) +
geom_tile(aes(fill = var2))
}
# create geom_point for found ortho; coloring by var1 or
# orthoIDs (only when working on lowest taxonomy rank)
# and inparalogs (co-orthologs)
if (length(unique(stats::na.omit(data$presSpec))) < 2) {
# working on the lowest taxonomy rank
if (parm$colorByOrthoID == TRUE) {
# color by ortho IDs
p <- p + geom_point(
aes(colour = factor(orthoFreq)), na.rm = TRUE,
size = data$presSpec*5*(1+parm$dotZoom), show.legend = TRUE
)
} else {
if (length(unique(stats::na.omit(data$var1))) == 1) {
p <- p + geom_point(
aes(colour = var1), na.rm = TRUE,
size = data$presSpec*5*(1+parm$dotZoom), show.legend = FALSE
)
} else {
p <- p +
geom_point(
aes(colour = var1), na.rm = TRUE,
size = data$presSpec * 5 * (1 + parm$dotZoom)) +
scale_color_gradient2(
low = parm$lowColorVar1, high = parm$highColorVar1,
mid = parm$midColorVar1, midpoint = parm$midVar1,
limits = c(0,1)
)
}
# plot inparalogs (if available)
if (length(unique(stats::na.omit(data$paralog))) > 0) {
p <- p +
geom_point(
data = data, aes(size = paralog), color=parm$paraColor,
na.rm = TRUE, show.legend = TRUE) +
guides(size = guide_legend(title = "# of co-orthologs")) +
scale_size_continuous(range = c(
min(stats::na.omit(data$paralogSize))*(1+parm$dotZoom),
max(stats::na.omit(data$paralogSize))*(1+parm$dotZoom)))
}
}
} else {
# scale dot size based on % preSpec in each super taxon
if (length(unique(stats::na.omit(data$var1))) == 1) {
p <- p + geom_point(aes(size=presSpec),color="#336a98",na.rm = TRUE)
} else {
p <- p + geom_point(aes(colour=var1, size = presSpec),na.rm = TRUE)+
scale_color_gradient2(
low = parm$lowColorVar1, high = parm$highColorVar1,
mid = parm$midColorVar1, midpoint = parm$midVar1,
limits = c(0,1)
)
}
# remain the scale of point while filtering % presSpec
presentVl <- data$presSpec[!is.na(data$presSpec)]
p <- p + scale_size_continuous(range = c(
(floor(min(presentVl) * 10) / 10 * 5) * (1 + parm$dotZoom),
(floor(max(presentVl) * 10) / 10 * 5) * (1 + parm$dotZoom)))
}
# create legend
if (parm$colorByGroup == FALSE) {
if (parm$colorByOrthoID == FALSE) {
p <- p + guides(fill = guide_colourbar(title = parm$var2ID),
color = guide_colourbar(title = parm$var1ID))
} else {
p <- p + guides(fill = guide_colourbar(title = parm$var2ID),
color = guide_legend(title = 'OrthoID copy number'))
}
} else {
p <- p + guides(fill = guide_legend("Category"),
color = guide_colourbar(title = parm$var1ID))
}
# guideline for separating ref species
if (parm$guideline == 1) {
if (parm$xAxis == "genes") {
p <- p + labs(y = "Taxon") +
geom_hline(yintercept = 0.5, colour = "dodgerblue4") +
geom_hline(yintercept = 1.5, colour = "dodgerblue4")
} else
p <- p + labs(x = "Taxon") +
geom_vline(xintercept = 0.5, colour = "dodgerblue4") +
geom_vline(xintercept = 1.5, colour = "dodgerblue4")
}
# text size, legend position
p <- p + theme_minimal(base_size = 9)
vjustValue <- 1
if (parm$xAngle == 90) vjustValue <- 0.5
p <- p + theme(
axis.text.x = element_text(
angle = parm$xAngle, hjust = 1, size = parm$xSize,
vjust = vjustValue
),
axis.text.y = element_text(size = parm$ySize),
axis.title.x = element_text(size = parm$xSize),
axis.title.y = element_text(size = parm$ySize),
legend.title = element_text(size = parm$legendSize),
legend.text = element_text(size = parm$legendSize),
legend.position = parm$mainLegend)
return(p)
}
#' Highlight gene and/or taxon of interest on the phylogenetic profile plot
#' @export
#' @usage highlightProfilePlot(profilePlot = NULL, plotDf = NULL,
#' taxonHighlight = "none", workingRank = "none", geneHighlight = NULL,
#' taxDB = NULL, xAxis = "taxa")
#' @param profilePlot initial (highlighted) profile plot
#' @param plotDf dataframe for plotting the heatmap phylogentic profile
#' @param taxonHighlight taxon of interst. Default = "none".
#' @param workingRank working taxonomy rank (needed only for highlight taxon).
#' @param geneHighlight gene of interest. Default = NULL.
#' @param taxDB Path to the taxonomy DB files
#' @param xAxis type of x-axis (either "genes" or "taxa")
#' @return A profile heatmap plot with highlighted gene and/or taxon of interest
#' as ggplot object.
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{dataMainPlot}}, \code{\link{dataCustomizedPlot}},
#' \code{\link{heatmapPlotting}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' plotDf <- dataMainPlot(finalProcessedProfile)
#' plotParameter <- list(
#' "xAxis" = "taxa",
#' "var1ID" = "FAS_FW",
#' "var2ID" = "FAS_BW",
#' "midVar1" = 0.5,
#' "midColorVar1" = "#FFFFFF",
#' "lowColorVar1" = "#FF8C00",
#' "highColorVar1" = "#4682B4",
#' "midVar2" = 1,
#' "midColorVar2" = "#FFFFFF",
#' "lowColorVar2" = "#CB4C4E",
#' "highColorVar2" = "#3E436F",
#' "paraColor" = "#07D000",
#' "xSize" = 8,
#' "ySize" = 8,
#' "legendSize" = 8,
#' "mainLegend" = "top",
#' "dotZoom" = 0,
#' "xAngle" = 60,
#' "guideline" = 0,
#' "colorByGroup" = FALSE,
#' "colorByOrthoID" = FALSE
#' )
#' profilePlot <- heatmapPlotting(plotDf, plotParameter)
#' taxonHighlight <- "none"
#' workingRank <- "class"
#' geneHighlight <- "100265at6656"
#' highlightProfilePlot(
#' profilePlot, plotDf, taxonHighlight, workingRank, geneHighlight,
#' NULL, plotParameter$xAxis
#' )
highlightProfilePlot <- function(
profilePlot = NULL, plotDf = NULL, taxonHighlight = "none",
workingRank = "none", geneHighlight = NULL, taxDB = NULL, xAxis = "taxa"
){
if (is.null(plotDf)) stop("Input data cannot be NULL!")
if (is.null(profilePlot)) stop("Profile plot cannot be NULL!")
xmin <- xmax <- ymin <- ymax <- NULL
if (is.null(taxonHighlight) && is.null(geneHighlight)) return(profilePlot)
# highlight taxon
if (length(taxonHighlight) > 0 && !("none" %in% taxonHighlight)) {
# get selected highlight taxon ID
taxName <- getNameList(taxDB)
taxonHighlightID <- taxName$ncbiID[
taxName$fullName %in% taxonHighlight & taxName$rank == workingRank]
if (length(taxonHighlightID) == 0L) {
taxonHighlightID <- taxName$ncbiID[
taxName$fullName %in% taxonHighlight
]
} else if(length(taxonHighlightID) < length(taxonHighlight)) {
missingID <- taxName$ncbiID[
taxName$fullName %in% taxonHighlight
]
missingID <- missingID[!(missingID %in% taxonHighlightID)]
taxonHighlightID <- c(taxonHighlightID, missingID)
}
# get taxonID together with it sorted index
selTaxon <- unique(as.character(
plotDf$supertaxon[plotDf$supertaxonID %in% taxonHighlightID]
))
selIndex <- match(selTaxon, levels(as.factor(plotDf$supertaxon)))
if (xAxis == "taxa") {
rect <- data.frame(
xmin=selIndex-0.5, xmax = selIndex+0.5, ymin = -Inf, ymax = Inf)
} else
rect <- data.frame(
ymin=selIndex-0.5, ymax = selIndex+0.5, xmin = -Inf, xmax = Inf)
profilePlot <- profilePlot + geom_rect(
data = rect, color = "yellow", alpha = 0.3, inherit.aes = FALSE,
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax))
}
# highlight gene
if (length(geneHighlight) > 0 && !("none" %in% geneHighlight)) {
selIndex <- match(geneHighlight, levels(as.factor(plotDf$geneID)))
if (xAxis == "taxa") {
rect <- data.frame(
ymin=selIndex-0.5, ymax = selIndex+0.5, xmin = -Inf, xmax = Inf)
} else
rect <- data.frame(
xmin=selIndex-0.5, xmax = selIndex+0.5, ymin = -Inf, ymax = Inf)
profilePlot <- profilePlot + geom_rect(
data = rect, color = "yellow", alpha = 0.3, inherit.aes = FALSE,
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax))
}
return(profilePlot)
}
#' Add taxonomy rank division lines to the heatmap plot
#' @export
#' @usage addRankDivisionPlot(profilePlot = NULL, plotDf = NULL,
#' taxDB = NULL, workingRank = NULL, superRank = NULL, xAxis = "taxa",
#' groupLabelSize = 14, groupLabelDist = 2, groupLabelAngle = 90)
#' @param profilePlot initial (highlighted) profile plot
#' @param plotDf dataframe for plotting the heatmap phylogentic profile
#' @param taxDB path to taxonomy database (taxonomyMatrix.txt file required!)
#' @param workingRank working taxonomy rank (e.g. species)
#' @param superRank taxonomy rank for division lines (e.g. superkingdom)
#' @param xAxis type of x-axis (either "genes" or "taxa")
#' @param groupLabelSize size of rank labels
#' @param groupLabelDist size of the plot area for rank labels
#' @param groupLabelAngle angle of rank labels
#' @return A profile heatmap plot with highlighted gene and/or taxon of interest
#' as ggplot object.
#' @author Vinh Tran {tran@bio.uni-frankfurt.de}
#' @seealso \code{\link{heatmapPlotting}}, \code{\link{highlightProfilePlot}},
#' \code{\link{getTaxonomyMatrix}}
#' @examples
#' data("finalProcessedProfile", package="PhyloProfile")
#' plotDf <- dataMainPlot(finalProcessedProfile)
#' plotParameter <- list(
#' "xAxis" = "taxa",
#' "var1ID" = "FAS_FW",
#' "var2ID" = "FAS_BW",
#' "midVar1" = 0.5,
#' "midColorVar1" = "#FFFFFF",
#' "lowColorVar1" = "#FF8C00",
#' "highColorVar1" = "#4682B4",
#' "midVar2" = 1,
#' "midColorVar2" = "#FFFFFF",
#' "lowColorVar2" = "#CB4C4E",
#' "highColorVar2" = "#3E436F",
#' "paraColor" = "#07D000",
#' "xSize" = 8,
#' "ySize" = 8,
#' "legendSize" = 8,
#' "mainLegend" = "top",
#' "dotZoom" = 0,
#' "xAngle" = 60,
#' "guideline" = 0,
#' "colorByGroup" = FALSE,
#' "colorByOrthoID" = FALSE
#' )
#' profilePlot <- heatmapPlotting(plotDf, plotParameter)
#' workingRank <- "class"
#' superRank <- "superkingdom"
#' addRankDivisionPlot(
#' profilePlot, plotDf, NULL, workingRank, superRank, "taxa"
#' )
addRankDivisionPlot <- function(
profilePlot = NULL, plotDf = NULL, taxDB = NULL,
workingRank = NULL, superRank = NULL, xAxis = "taxa",
groupLabelSize = 14, groupLabelDist = 2, groupLabelAngle = 90
) {
if (is.null(plotDf)) stop("Input data cannot be NULL!")
if (is.null(profilePlot)) stop("Profile plot cannot be NULL!")
if (is.null(workingRank) || is.null(superRank)) {
# guideline for separating ref species
if (xAxis == "genes") {
profilePlot <- profilePlot + labs(y = "Taxon") +
geom_hline(yintercept = 0.5, colour = "dodgerblue4") +
geom_hline(yintercept = 1.5, colour = "dodgerblue4")
} else
profilePlot <- profilePlot + labs(x = "Taxon") +
geom_vline(xintercept = 0.5, colour = "dodgerblue4") +
geom_vline(xintercept = 1.5, colour = "dodgerblue4")
return(profilePlot)
} else {
# sort supertaxonID based on the sorted supertaxon
plotDf <- plotDf[with(plotDf,order(supertaxon)),]
plotDf$supertaxonID <- factor(
plotDf$supertaxonID, levels = unique(plotDf$supertaxonID)
)
# get input (super)taxa
inputTax <- levels(as.factor(plotDf$supertaxonID))
# subset taxonomy matrix to contain only superrank for division line
taxMatrix <- getTaxonomyMatrix(taxDB)
subTaxMatrix <- subset(
taxMatrix[taxMatrix[[workingRank]] %in% inputTax,],
select = c(as.character(workingRank), as.character(superRank))
)
subTaxMatrix <- subTaxMatrix[!duplicated(subTaxMatrix),]
# remove IDs that do not have real NCBI superRank
nameList <- getNameList(taxDB)
subNameList <- nameList[
nameList$ncbiID %in% subTaxMatrix[[superRank]],
c("ncbiID", "rank", "fullName")
]
colnames(subNameList) <- c(superRank, "rank", "name")
mergedDf <- merge(subTaxMatrix, subNameList, by = superRank, all.x=TRUE)
mergedDf <- mergedDf[mergedDf$rank == superRank,]
subTaxMatrix <- mergedDf
# group input taxa based on superrank and get their index
groupedList <- lapply(
levels(as.factor(subTaxMatrix[[superRank]])),
function(x) {
tmp <- subTaxMatrix[subTaxMatrix[[superRank]] == x,]
tmp$index <- which(
levels(as.factor(plotDf$supertaxonID))
%in% tmp[[workingRank]]
)
return(tmp)
}
)
# add vertical line to divide taxon groups
# add vertical line to divide taxon groups
max_taxa <- length(unique(as.character(plotDf$geneID)))
for(i in groupedList) {
min <- min(i$index)
max <- max(i$index)
if (xAxis == "taxa") {
profilePlot <- profilePlot +
geom_vline(xintercept = min - 0.5, colour = "dodgerblue4") +
geom_vline(xintercept = max + 0.5, colour = "dodgerblue4") +
annotate(
geom = "text", angle = groupLabelAngle, hjust = 0,
size = groupLabelSize,
x = min,
y = max_taxa + 0.5,
label = unique(as.character(i$name))
)
} else {
profilePlot <- profilePlot +
geom_hline(yintercept = min - 0.5, colour = "dodgerblue4") +
geom_hline(yintercept = max + 0.5, colour = "dodgerblue4") +
annotate(
geom = "text", angle = groupLabelAngle - 90, hjust = 0,
size = groupLabelSize,
y = min,
x = max_taxa + 1,
label = unique(as.character(i$name))
)
}
}
if (xAxis == "taxa") {
return(
profilePlot + coord_cartesian(
clip = 'off', ylim = c(1, max_taxa + groupLabelDist)
)
)
} else
return(
profilePlot + coord_cartesian(
clip = 'off', xlim = c(1, max_taxa + groupLabelDist)
)
)
}
}
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