tsne: tsne: A t-SNE function

In M3C: Monte Carlo Reference-based Consensus Clustering

Description

This is a flexible t-SNE function that can be run on a standard data frame. It is a wrapper for Rtsne/ggplot2 code and can be customised with different colours and font sizes and more.

Usage

tsne(mydata, labels = FALSE, perplex = 15, printres = FALSE,
  seed = FALSE, axistextsize = 18, legendtextsize = 18,
  dotsize = 5, textlabelsize = 4, legendtitle = "Group",
  controlscale = FALSE, scale = 1, low = "grey", high = "red",
  colvec = c("skyblue", "gold", "violet", "darkorchid", "slateblue",
  "forestgreen", "violetred", "orange", "midnightblue", "grey31", "black"),
  printheight = 20, printwidth = 22, text = FALSE)

Arguments

mydata	Data frame or matrix: if dataframe/matrix should have samples as columns and rows as features
labels	Character vector: if we want to just label with gender for example
perplex	Numerical value: perplexity value that Rtsne uses internally
printres	Logical flag: whether to print the t-SNE into current directory
seed	Numerical value: optionally set the seed
axistextsize	Numerical value: axis text size
legendtextsize	Numerical value: legend text size
dotsize	Numerical value: dot size
textlabelsize	Numerical value: text inside plot label size
legendtitle	Character vector: text legend title
controlscale	Logical flag: whether to control the colour scale
scale	Numerical value: 1=spectral palette, 2=manual low and high palette, 3=categorical labels
low	Character vector: continuous scale low colour
high	Character vector: continuous scale high colour
colvec	Character vector: a series of colours in vector for categorical labels, e.g. c("sky blue", "gold")
printheight	Numerical value: png height
printwidth	Numerical value: png width
text	Character vector: if we wanted to label the samples with text IDs to look for outliers

Value

A t-SNE plot object

Examples

TSNE <- tsne(mydata,perplex=15)

Example output

***t-SNE wrapper function***
running...
done.

M3C documentation built on Nov. 8, 2020, 6:50 p.m.