easylabel

A common problem in R is labelling scatter plots with large numbers of points and/or labels. We provide a utility for easy labelling of scatter plots, and quick plotting of volcano plots and MA plots for gene expression analyses as well as Manhattan plots for genetic analyses. Using an interactive shiny and plotly interface, users can hover over points to see where specific points are located and click on points to easily label them. Labels can be toggled on/off simply by clicking. An input box and batch input window provides an easy way to label points by name. Labels can be dragged around the plot to place them optimally, and the finished plot can be easily exported directly to PDF for publication. Plots and labels are highly customisable allowing for control over label and line colour with options including rounded label boxes and matching of label colours to point colours.

Installation

Install from CRAN

install.packages("easylabel")
library(easylabel)

Install from Github

devtools::install_github("myles-lewis/easylabel")

If you wish to use the optional useQ function with easyVolcano() and easyMAplot(), you will need to install additional package qvalue from Bioconductor:

if (!requireNamespace("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
BiocManager::install("qvalue")

If you wish to use the optional fullGeneNames function, you will need to install packages AnnotationDbi and org.Hs.eg.db from Bioconductor:

BiocManager::install("AnnotationDbi")
BiocManager::install("org.Hs.eg.db")

Quick start

Simple instructions:

Hover over and click on/off genes which you want to label.
When you have selected all your chosen genes, then drag gene names to move label positions.
Click the save button to export a PDF in base graphics.

To export an SVG from plotly:

Switch to SVG when finalised (only do this at last moment as otherwise editing is very slow).
Press camera button in modebar to save image as SVG.

Examples

Simple scatter plot

Simple scatter plot from the gapminder dataset setting colours and marker shapes and introducing the shiny app for clicking on points to set labels and dragging labels around to position them.

# gapminder data set
if(!require(gapminder)) {install.packages("gapminder")}
library(gapminder)
easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
          col = 'continent', shape = 'continent',
          size = 10,
          labs = 'country', 
          zeroline = FALSE)

Bubble chart

size can be set to a column in the dataset to create a bubble chart.

library(gapminder)
easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
          col = 'continent', labs = 'country', 
          size = 'pop',
          alpha = 0.6,
          zeroline = FALSE)

Volcano plots

Volcano plots can be quickly and easily created from results objects directly from DESeq2 and limma.

volc1 <- results(DESeq2_dds)
easyVolcano(volc1, fccut = 0)

myles-lewis / easylabel