R/defunct_phenotype_plot.R
In ekawaler/simplePheWAS:
# # The same as phenotypePlot, but uses ggrepel to keep labels from overlapping.
# # Defunct - ggrepel now in the PheWAS package
#
# phenotype_plot <-
# function(d, max.y,max.x, suggestive.line, significant.line,
# size.x.labels=9, size.y.labels=9, switch.axis=F, sort.by.value=F, sort.by.category.value=F,
# #annotation
# annotate.phenotype.description,
# annotate.angle=30, annotate.size=5, annotate.level,
# annotate.phenotype=F,
# annotate.snp.w.phenotype=F,
# annotate.snp=F, annotate.snp.angle=0,
# annotate.list, annotate.only.largest=T,
# #labels
# lc.labels=F,
# x.group.labels=T, x.phenotype.labels=F,
# sizes=F, direction=F, point.size=3,
# #plot characteristics
# use.color=T,
# color.palette,
# title= paste0("Phenotype Plot ", date()),
# x.axis.label="Phenotypes",
# y.axis.label="Values",
# y.axis.interval=5) {
# #Check to ensure the input contains columns phenotype and value
# if ( sum(c("phenotype","value") %in% names(d))<2 ) stop("Data input must contain columns phenotype and value.")
# #Check for annotation information
# if (!missing(annotate.phenotype.description)) {
# if(class(annotate.phenotype.description)=="data.frame" & sum(c("phenotype","description") %in% names(annotate.phenotype.description))==2) {
# #Add annotation
# d=merge(d,annotate.phenotype.description)
# annotate.phenotype.description=T
# } else if(annotate.phenotype.description==T & length(d$description)) {
# #Do nothing, as it is ready.
# } else {
# annotate.phenotype.description=F
# stop("Annotate.phenotype must contain columns phenotype and description, or be TRUE with provided d$description.")
# }
# } else {
# annotate.phenotype.description=F
# }
# if ((annotate.snp|annotate.snp.w.phenotype) & !("snp" %in% names(d))) stop("You requested SNP annotation but d$snp is not defined.")
# if(annotate.snp.w.phenotype&annotate.snp) warning("You requested SNP annotation twice")
#
# #Is there any annotation?
# annotate=annotate.phenotype.description|annotate.phenotype|annotate.snp|annotate.snp.w.phenotype
# #If so, but nothing listing to annotate, warn and remove annotate flag
# if(annotate&missing(annotate.level)&missing(annotate.list)) {
# warning("You requested annotation, but did not specify annotate.level or annotate.list.")
# annotate=F
# }
# #Check for conflicting color commands
# if(!use.color & !missing(color.palette)) stop("You requested no color, but provided a color palette.")
# #Check for color
# if(use.color) {
# if(missing(color.palette)) {
# if(!("color" %in% names(d))) stop("You requested color, but did not provide a color attribute in d or color.palette")
# else if(class(d$color)=="factor") warning("The color attribute is a factor and no color palette is provided: R default color scheme will be used. Convert color to character if it contains color names or codes")
# }
# #Set up color if using a palette
# if(!missing(color.palette)&!length(d$color)) {
# if(length(d$groupnum)) d$color=d$groupnum
# else stop("You requested use.color, but d$color or d$groupnum were not provided to distinguish groups.")
# }
# } else {
# #Set the colors to all black if no color is requested
# d$color="#000000"
# }
#
# #Check for point sizing/direction information if requested
# if(sizes&!length(d$size)) stop("You requested size information, but did not provide d$size")
# if(direction&!length(d$direction)) stop("You requested direction information, but did not provide d$direction")
# #Set point size if sizes are not requested
# if(!sizes) d$size=point.size
#
# #Remove lc.labels flag if no annotations
# if(!annotate.phenotype.description&!annotate.phenotype&!annotate.snp&!annotate.snp.w.phenotype) lc.labels=F
#
# #One cannot sort by value and have x.group.labels
# if (sort.by.value & x.group.labels) stop("One cannot sort universally by value and have x group labels. Try sort.by.category.value or not labeling the groups.")
# #Check for group information if requested
# if((sort.by.category.value|x.group.labels)&(sum(c("groupnum","group") %in% names(d))<2)) {
# stop("Requested group information, but did not provide d$groupnum and d$group.")
# }
#
# #If no group info, just assign all to group 0
# if(!("groupnum"%in%names(d))) {
# d$groupnum=0
# }
#
# #Remove items with NA values or phenotypes
# d=d[!(is.na(d$phenotype)|is.na(d$value)),]
#
# #Sort by the phenotype
# d=d[order(d$phenotype),]
#
# #Set the maximum x value to fit all phenotypes if not specified
# if(missing(max.x)) max.x = length(unique(d$phenotype))
#
#
# #Create the list of phenotypes, finding the best values for each phenotype
# phenotypes=aggregate(value ~ phenotype + groupnum, d,FUN=max)
# #Remove the least significant phenotypes; only has an effect if max.x was specified.
# phenotypes=phenotypes[order(phenotypes$value, decreasing=T),][1:min(nrow(phenotypes),max.x),]
#
# #If the user requested sorting by values
# if (sort.by.value) {
# #Sort by values
# phenotypes=phenotypes[order(phenotypes$value, decreasing=T),]
# } else if (sort.by.category.value) {
# #If the user requested soring by values within each group.
# #Sort by group and then value
# phenotypes=phenotypes[order(-phenotypes$groupnum,phenotypes$value, decreasing=T),]
# } else {
# #Restore the phenotype sorting order if no other sorting was requested
# #TODO: What about non-numeric phenotypes? Need this to sort 008 etc.
# phenotypes=phenotypes[order(phenotypes$phenotype),]
# }
#
# phenotypes$seq = 1:nrow(phenotypes)
#
#
# #Limit to phenotype and seq, as they are the only relevant columns
# #Include value as min.value for annotation purposes
# phenotypes=phenotypes[,c("phenotype","seq","value")]
# names(phenotypes)[3]="min.value"
#
# #Add sequence information
# d=inner_join(phenotypes,d,by="phenotype")
# d=d[order(d$seq),]
#
# #Define the max y axis value if not provided
# if(missing(max.y)) max.y=ceiling(max(d$value))
#
# if(switch.axis) {
# #Swap ordering
# d=d[nrow(d):1,]
# d$groupnum=max(d$groupnum)-d$groupnum+1
# d$seq=max(d$seq)-d$seq+1
# }
#
# if (x.group.labels) {
# labels=bind_rows(by(d,d$groupnum,function(x){data.frame(tick=mean(unique(x$seq)),label=as.character(x$group[1]),stringsAsFactors=F)}))
# labels=labels[order(labels$tick),]
# }
#
# if(missing(color.palette)) {
# color.palette = unique(d[order(d$seq),]$color)
# names(color.palette)=color.palette
# } else {
# names(color.palette) = unique(d[order(d$seq),]$color)
# }
#
#
# #Check if we are using switch.axis
# if(!switch.axis) {
# #Generate the inital plot
# plot=ggplot(d,ylab=y.axis.label,xlab=x.axis.label)
#
# #Include lines for significance thresholds
# if (!missing(suggestive.line)&!is.na(suggestive.line)) plot=plot+geom_hline(yintercept=suggestive.line,colour="blue", alpha=I(1/3),size=1)
# if (!missing(significant.line)&!is.na(significant.line)) plot=plot+geom_hline(yintercept=significant.line,colour="red",alpha=I(1/3),size=1)
#
# plot=plot+aes(seq,value,size=size,colour=color)
# if(!sizes) plot=plot+scale_size(range=c(point.size,point.size),guide="none")
# #Add points
# plot=plot+geom_point()
#
# #Color as defined
# plot = plot + scale_colour_manual(values= color.palette, guide="none")
#
# #If label the X axis with the groups if requested
# if (x.group.labels) {
#
# plot=plot+scale_x_continuous(name=x.axis.label, limits=c(1,max.x), breaks=labels$tick, labels=labels$label, expand=c(.01,0))
#
# } else {
# plot=plot+scale_x_continuous(name=x.axis.label, limits=c(1,max.x), breaks=c(-100), labels=c(""), expand=c(.015,0))
# }
#
# #Set the Y scale and labels
# plot=plot+scale_y_continuous(y.axis.label, limits=c(0,max.y), breaks=seq(0,max.y,y.axis.interval), expand=c(0,.2))
#
# #Set the default theme
# plot=plot+theme(
# panel.background=element_blank(),
# panel.grid.minor=element_blank(),
# axis.text.x=element_text(size=size.x.labels, colour="black", angle=-40, hjust=0, vjust=1),
# axis.text.y=element_text(size=size.y.labels, colour="black"),
# axis.line =element_line(colour="black"),
# axis.ticks=element_line(colour="black")
# )
# } else {
# ####Generate plot with switch.axis
#
# #Generate the inital plot
# plot=ggplot(d,xlab=y.axis.label,ylab=x.axis.label)
#
# #Include lines for significance thresholds
# if (!missing(suggestive.line)&!is.na(suggestive.line)) plot=plot+geom_vline(xintercept=suggestive.line,colour="blue", alpha=I(1/3),size=1)
# if (!missing(significant.line)&!is.na(significant.line)) plot=plot+geom_vline(xintercept=significant.line,colour="red",alpha=I(1/3),size=1)
#
# plot=plot+aes(value,seq,size=size,colour=color)
# if(!sizes) plot=plot+scale_size(range=c(point.size,point.size),guide="none")
# #Add points
# plot=plot+geom_point()
#
#
# #Color as defined
# plot = plot + scale_colour_manual(values= color.palette, guide="none")
#
# #If label the Y axis with the groups if requested
# if (x.group.labels) {
# plot=plot+scale_y_continuous(name=x.axis.label, limits=c(1,max.x), breaks=labels$tick, labels=labels$label, expand=c(.015,.02))
#
# } else {
# plot=plot+scale_y_continuous(name=x.axis.label, limits=c(0,max.x), breaks=c(-100), labels=c(""), expand=c(.015,0))
# }
#
# #Set the Y scale and labels
# plot=plot+scale_x_continuous(y.axis.label, limits=c(0,max.y), breaks=seq(0,max.y,y.axis.interval), expand=c(0,.2))
#
# #Set the default theme
# plot=plot+theme(
# panel.background=element_blank(),
# panel.grid.minor=element_blank(),
# axis.text.y=element_text(size=size.x.labels, colour="black", hjust=1, vjust=.5),
# axis.text.x=element_text(size=size.y.labels, colour="black", hjust=.5, vjust=0),
# axis.line =element_line(colour="black"),
# axis.ticks=element_line(colour="black")
# )
# }
#
# #Hide the legend by default
# plot = plot+theme(legend.position = "none")
#
# #Add OR information
# if(sizes){
# plot= suppressWarnings(plot + theme(legend.position="right") +
# scale_size("Size", range = c(point.size, 2*point.size)))
# }
# if(direction){
# plot=plot+aes(shape = factor(direction), fill=color) +
# scale_shape("Direction", solid = TRUE) + scale_shape_manual(values=c(25,24)) +
# scale_fill_manual(values= color.palette, guide="none")
# }
# #If annotation present, start the definitions, otherwise skip it
# if (annotate) {
# d$annotate=F
# #If provided with a list of phenotypes to annotate, select those.
# if(!missing(annotate.list)) d[d$phenotype %in% annotate.list, ]$annotate=T
# #Include those above the given threshold
# if((!missing(annotate.level))&(sum(d$value>=annotate.level)>0)) d[d$value>=annotate.level, ]$annotate=T
# #Select only the largest value for each phenotype to label, unless requested otherwise
# if(sum(d$value!=d$min.value)>0&annotate.only.largest) d[d$value!=d$min.value,]$annotate=F
# #If no base descriptions were included, add empty ones
# if(!annotate.phenotype.description) {
# d$description=""
# }
# #If requested the phenotype annotation, add it
# if(annotate.phenotype) d$description = d$phenotype %+% ifelse(d$description=="","",":" %+% d$description )
#
# #Add snp annotation to the phenotype label
# if (annotate.snp.w.phenotype) d$description = d$snp %+% ifelse(d$description=="","",":" %+% d$description )
#
# #Cap annotation length
# d$description = substr(d$description,1,60)
# #Add leading space
# d$description = paste0(" ",d$description)
# #If lower case labels are requested, lower case them.
# if(lc.labels) d$description=tolower(d$description)
# if(sum(d$annotate)==0) {
# warning("Annotation requested, but no points met criteria")
# } else {
# #Add annotations
# if(annotate.phenotype.description|annotate.phenotype|annotate.snp.w.phenotype) plot = plot + ggrepel::geom_text_repel(aes(label=description),colour="black",data=d[d$annotate,],size=annotate.size,angle=annotate.angle)
# #Add SNP annotations
# if(annotate.snp) plot = plot + ggrepel::geom_text_repel(aes(label=snp),colour="black",data=d[d$annotate,],size=annotate.size,angle=annotate.snp.angle)
# }
# }
#
# #Add the title
# plot=plot+labs(title=title) + theme(title=element_text(size=12))
#
# plot
# }
ekawaler/simplePheWAS documentation built on May 16, 2019, 2:24 a.m.
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# # The same as phenotypePlot, but uses ggrepel to keep labels from overlapping.
# # Defunct - ggrepel now in the PheWAS package
#
# phenotype_plot <-
# function(d, max.y,max.x, suggestive.line, significant.line,
# size.x.labels=9, size.y.labels=9, switch.axis=F, sort.by.value=F, sort.by.category.value=F,
# #annotation
# annotate.phenotype.description,
# annotate.angle=30, annotate.size=5, annotate.level,
# annotate.phenotype=F,
# annotate.snp.w.phenotype=F,
# annotate.snp=F, annotate.snp.angle=0,
# annotate.list, annotate.only.largest=T,
# #labels
# lc.labels=F,
# x.group.labels=T, x.phenotype.labels=F,
# sizes=F, direction=F, point.size=3,
# #plot characteristics
# use.color=T,
# color.palette,
# title= paste0("Phenotype Plot ", date()),
# x.axis.label="Phenotypes",
# y.axis.label="Values",
# y.axis.interval=5) {
# #Check to ensure the input contains columns phenotype and value
# if ( sum(c("phenotype","value") %in% names(d))<2 ) stop("Data input must contain columns phenotype and value.")
# #Check for annotation information
# if (!missing(annotate.phenotype.description)) {
# if(class(annotate.phenotype.description)=="data.frame" & sum(c("phenotype","description") %in% names(annotate.phenotype.description))==2) {
# #Add annotation
# d=merge(d,annotate.phenotype.description)
# annotate.phenotype.description=T
# } else if(annotate.phenotype.description==T & length(d$description)) {
# #Do nothing, as it is ready.
# } else {
# annotate.phenotype.description=F
# stop("Annotate.phenotype must contain columns phenotype and description, or be TRUE with provided d$description.")
# }
# } else {
# annotate.phenotype.description=F
# }
# if ((annotate.snp|annotate.snp.w.phenotype) & !("snp" %in% names(d))) stop("You requested SNP annotation but d$snp is not defined.")
# if(annotate.snp.w.phenotype&annotate.snp) warning("You requested SNP annotation twice")
#
# #Is there any annotation?
# annotate=annotate.phenotype.description|annotate.phenotype|annotate.snp|annotate.snp.w.phenotype
# #If so, but nothing listing to annotate, warn and remove annotate flag
# if(annotate&missing(annotate.level)&missing(annotate.list)) {
# warning("You requested annotation, but did not specify annotate.level or annotate.list.")
# annotate=F
# }
# #Check for conflicting color commands
# if(!use.color & !missing(color.palette)) stop("You requested no color, but provided a color palette.")
# #Check for color
# if(use.color) {
# if(missing(color.palette)) {
# if(!("color" %in% names(d))) stop("You requested color, but did not provide a color attribute in d or color.palette")
# else if(class(d$color)=="factor") warning("The color attribute is a factor and no color palette is provided: R default color scheme will be used. Convert color to character if it contains color names or codes")
# }
# #Set up color if using a palette
# if(!missing(color.palette)&!length(d$color)) {
# if(length(d$groupnum)) d$color=d$groupnum
# else stop("You requested use.color, but d$color or d$groupnum were not provided to distinguish groups.")
# }
# } else {
# #Set the colors to all black if no color is requested
# d$color="#000000"
# }
#
# #Check for point sizing/direction information if requested
# if(sizes&!length(d$size)) stop("You requested size information, but did not provide d$size")
# if(direction&!length(d$direction)) stop("You requested direction information, but did not provide d$direction")
# #Set point size if sizes are not requested
# if(!sizes) d$size=point.size
#
# #Remove lc.labels flag if no annotations
# if(!annotate.phenotype.description&!annotate.phenotype&!annotate.snp&!annotate.snp.w.phenotype) lc.labels=F
#
# #One cannot sort by value and have x.group.labels
# if (sort.by.value & x.group.labels) stop("One cannot sort universally by value and have x group labels. Try sort.by.category.value or not labeling the groups.")
# #Check for group information if requested
# if((sort.by.category.value|x.group.labels)&(sum(c("groupnum","group") %in% names(d))<2)) {
# stop("Requested group information, but did not provide d$groupnum and d$group.")
# }
#
# #If no group info, just assign all to group 0
# if(!("groupnum"%in%names(d))) {
# d$groupnum=0
# }
#
# #Remove items with NA values or phenotypes
# d=d[!(is.na(d$phenotype)|is.na(d$value)),]
#
# #Sort by the phenotype
# d=d[order(d$phenotype),]
#
# #Set the maximum x value to fit all phenotypes if not specified
# if(missing(max.x)) max.x = length(unique(d$phenotype))
#
#
# #Create the list of phenotypes, finding the best values for each phenotype
# phenotypes=aggregate(value ~ phenotype + groupnum, d,FUN=max)
# #Remove the least significant phenotypes; only has an effect if max.x was specified.
# phenotypes=phenotypes[order(phenotypes$value, decreasing=T),][1:min(nrow(phenotypes),max.x),]
#
# #If the user requested sorting by values
# if (sort.by.value) {
# #Sort by values
# phenotypes=phenotypes[order(phenotypes$value, decreasing=T),]
# } else if (sort.by.category.value) {
# #If the user requested soring by values within each group.
# #Sort by group and then value
# phenotypes=phenotypes[order(-phenotypes$groupnum,phenotypes$value, decreasing=T),]
# } else {
# #Restore the phenotype sorting order if no other sorting was requested
# #TODO: What about non-numeric phenotypes? Need this to sort 008 etc.
# phenotypes=phenotypes[order(phenotypes$phenotype),]
# }
#
# phenotypes$seq = 1:nrow(phenotypes)
#
#
# #Limit to phenotype and seq, as they are the only relevant columns
# #Include value as min.value for annotation purposes
# phenotypes=phenotypes[,c("phenotype","seq","value")]
# names(phenotypes)[3]="min.value"
#
# #Add sequence information
# d=inner_join(phenotypes,d,by="phenotype")
# d=d[order(d$seq),]
#
# #Define the max y axis value if not provided
# if(missing(max.y)) max.y=ceiling(max(d$value))
#
# if(switch.axis) {
# #Swap ordering
# d=d[nrow(d):1,]
# d$groupnum=max(d$groupnum)-d$groupnum+1
# d$seq=max(d$seq)-d$seq+1
# }
#
# if (x.group.labels) {
# labels=bind_rows(by(d,d$groupnum,function(x){data.frame(tick=mean(unique(x$seq)),label=as.character(x$group[1]),stringsAsFactors=F)}))
# labels=labels[order(labels$tick),]
# }
#
# if(missing(color.palette)) {
# color.palette = unique(d[order(d$seq),]$color)
# names(color.palette)=color.palette
# } else {
# names(color.palette) = unique(d[order(d$seq),]$color)
# }
#
#
# #Check if we are using switch.axis
# if(!switch.axis) {
# #Generate the inital plot
# plot=ggplot(d,ylab=y.axis.label,xlab=x.axis.label)
#
# #Include lines for significance thresholds
# if (!missing(suggestive.line)&!is.na(suggestive.line)) plot=plot+geom_hline(yintercept=suggestive.line,colour="blue", alpha=I(1/3),size=1)
# if (!missing(significant.line)&!is.na(significant.line)) plot=plot+geom_hline(yintercept=significant.line,colour="red",alpha=I(1/3),size=1)
#
# plot=plot+aes(seq,value,size=size,colour=color)
# if(!sizes) plot=plot+scale_size(range=c(point.size,point.size),guide="none")
# #Add points
# plot=plot+geom_point()
#
# #Color as defined
# plot = plot + scale_colour_manual(values= color.palette, guide="none")
#
# #If label the X axis with the groups if requested
# if (x.group.labels) {
#
# plot=plot+scale_x_continuous(name=x.axis.label, limits=c(1,max.x), breaks=labels$tick, labels=labels$label, expand=c(.01,0))
#
# } else {
# plot=plot+scale_x_continuous(name=x.axis.label, limits=c(1,max.x), breaks=c(-100), labels=c(""), expand=c(.015,0))
# }
#
# #Set the Y scale and labels
# plot=plot+scale_y_continuous(y.axis.label, limits=c(0,max.y), breaks=seq(0,max.y,y.axis.interval), expand=c(0,.2))
#
# #Set the default theme
# plot=plot+theme(
# panel.background=element_blank(),
# panel.grid.minor=element_blank(),
# axis.text.x=element_text(size=size.x.labels, colour="black", angle=-40, hjust=0, vjust=1),
# axis.text.y=element_text(size=size.y.labels, colour="black"),
# axis.line =element_line(colour="black"),
# axis.ticks=element_line(colour="black")
# )
# } else {
# ####Generate plot with switch.axis
#
# #Generate the inital plot
# plot=ggplot(d,xlab=y.axis.label,ylab=x.axis.label)
#
# #Include lines for significance thresholds
# if (!missing(suggestive.line)&!is.na(suggestive.line)) plot=plot+geom_vline(xintercept=suggestive.line,colour="blue", alpha=I(1/3),size=1)
# if (!missing(significant.line)&!is.na(significant.line)) plot=plot+geom_vline(xintercept=significant.line,colour="red",alpha=I(1/3),size=1)
#
# plot=plot+aes(value,seq,size=size,colour=color)
# if(!sizes) plot=plot+scale_size(range=c(point.size,point.size),guide="none")
# #Add points
# plot=plot+geom_point()
#
#
# #Color as defined
# plot = plot + scale_colour_manual(values= color.palette, guide="none")
#
# #If label the Y axis with the groups if requested
# if (x.group.labels) {
# plot=plot+scale_y_continuous(name=x.axis.label, limits=c(1,max.x), breaks=labels$tick, labels=labels$label, expand=c(.015,.02))
#
# } else {
# plot=plot+scale_y_continuous(name=x.axis.label, limits=c(0,max.x), breaks=c(-100), labels=c(""), expand=c(.015,0))
# }
#
# #Set the Y scale and labels
# plot=plot+scale_x_continuous(y.axis.label, limits=c(0,max.y), breaks=seq(0,max.y,y.axis.interval), expand=c(0,.2))
#
# #Set the default theme
# plot=plot+theme(
# panel.background=element_blank(),
# panel.grid.minor=element_blank(),
# axis.text.y=element_text(size=size.x.labels, colour="black", hjust=1, vjust=.5),
# axis.text.x=element_text(size=size.y.labels, colour="black", hjust=.5, vjust=0),
# axis.line =element_line(colour="black"),
# axis.ticks=element_line(colour="black")
# )
# }
#
# #Hide the legend by default
# plot = plot+theme(legend.position = "none")
#
# #Add OR information
# if(sizes){
# plot= suppressWarnings(plot + theme(legend.position="right") +
# scale_size("Size", range = c(point.size, 2*point.size)))
# }
# if(direction){
# plot=plot+aes(shape = factor(direction), fill=color) +
# scale_shape("Direction", solid = TRUE) + scale_shape_manual(values=c(25,24)) +
# scale_fill_manual(values= color.palette, guide="none")
# }
# #If annotation present, start the definitions, otherwise skip it
# if (annotate) {
# d$annotate=F
# #If provided with a list of phenotypes to annotate, select those.
# if(!missing(annotate.list)) d[d$phenotype %in% annotate.list, ]$annotate=T
# #Include those above the given threshold
# if((!missing(annotate.level))&(sum(d$value>=annotate.level)>0)) d[d$value>=annotate.level, ]$annotate=T
# #Select only the largest value for each phenotype to label, unless requested otherwise
# if(sum(d$value!=d$min.value)>0&annotate.only.largest) d[d$value!=d$min.value,]$annotate=F
# #If no base descriptions were included, add empty ones
# if(!annotate.phenotype.description) {
# d$description=""
# }
# #If requested the phenotype annotation, add it
# if(annotate.phenotype) d$description = d$phenotype %+% ifelse(d$description=="","",":" %+% d$description )
#
# #Add snp annotation to the phenotype label
# if (annotate.snp.w.phenotype) d$description = d$snp %+% ifelse(d$description=="","",":" %+% d$description )
#
# #Cap annotation length
# d$description = substr(d$description,1,60)
# #Add leading space
# d$description = paste0(" ",d$description)
# #If lower case labels are requested, lower case them.
# if(lc.labels) d$description=tolower(d$description)
# if(sum(d$annotate)==0) {
# warning("Annotation requested, but no points met criteria")
# } else {
# #Add annotations
# if(annotate.phenotype.description|annotate.phenotype|annotate.snp.w.phenotype) plot = plot + ggrepel::geom_text_repel(aes(label=description),colour="black",data=d[d$annotate,],size=annotate.size,angle=annotate.angle)
# #Add SNP annotations
# if(annotate.snp) plot = plot + ggrepel::geom_text_repel(aes(label=snp),colour="black",data=d[d$annotate,],size=annotate.size,angle=annotate.snp.angle)
# }
# }
#
# #Add the title
# plot=plot+labs(title=title) + theme(title=element_text(size=12))
#
# plot
# }
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