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43 lines
1.6 KiB
43 lines
1.6 KiB
\name{gglegend}
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\alias{gglegend}
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\title{gglegend}
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\usage{
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gglegend(data, x, y, var, stat="median", color="black", ...)
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}
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\arguments{
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\item{data}{A data frame from where to take x and y axis, and the grouping variable.}
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\item{x}{The variable that will be used for X axis in the heatmap.}
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\item{y}{The variable that will be used for Y axis in the heatmap.}
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\item{value}{The variable that will be used for grouping the heatmap. The labels will be taken from it}
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\item{stat}{The statistical central test that will be used to calculate the label coordinates. "mean" or "median" are posible, defaulting to "median".}
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\item{color}{The color of the labels, "black" by default. If NULL, nothig will be passed to the geom_label so it may be taken from aesthetics.}
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\item{...}{Other arguments that will be passed to the geom_label function.}
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}
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\description{
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Generates a geom_label object with labels in the center of each population or agrupation.
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}
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\examples{
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library(tidyverse)
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library(Rtsne)
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library(Rphenograph)
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library(igraph)
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## We will generate an example using tSNE and Phenograph algorithms, but can be applied to any other situation.
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iris_unique <- unique(iris) # Remove duplicates
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iris_matrix <- as.matrix(iris_unique[,1:4])
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# Set a seed if you want reproducible results
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set.seed(42)
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tsne_out <- Rtsne(iris_matrix,pca=FALSE,perplexity=30,theta=0.0) # Run TSNE
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rpheno<-Rphenograph(tsne_out$Y)
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df<-data.frame(as.data.frame(tsne_out$Y), "Clust"=factor(membership(rpheno[[2]])))
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head(df)
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ggplot(df, aes(V1,V2, color=Clust))+
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geom_point()+
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gglegend(df, V1, V2, Clust)+
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guides(color="none")
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}
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