- Gplots::venn(list(TMM = mydetmm, RLE = myderle, UQ = mydeuq)) There is a large overlap of differentially expressed genes in the different normalisation approaches. The normalisation factors were quite similar between all normalisation methods, which is why the results of the differential expression were quite concordant.
- Gplots: Various R Programming Tools for Plotting Data. Venn: Plot a Venn diagram: wapply: Compute the Value of a Function Over a Local Region Of An X-Y Plot.
A Venn diagram (aka Euler diagram) is a method of visualizing the amount of overlap between two (or three) lists of data, using circles to signify the size of each circle and positioning the circles such that the area of overlap represents the amount of list overlap. Create a Venn diagram and save it into a file. The function venn.diagram takes a list and creates a file containing a publication-quality Venn Diagram. Library (VennDiagram) venn.diagram (x, filename = 'venn-4-dimensions.png') Display the plot directly in R.
The gplots package provides Venn diagrams for up to five sets. Its input is a table that is produced by another function. The function venn() calls one after the other and is the only one to be seen by the user. The venn() function accepts either a list of sets as an argument, or it takes a binary matrix, one column per set, indicating for every element, one per row, the membership with every set.
The names of columns or the list elements are the set names. To squeeze extra circles in, those circles need to become ellipses. This works for four sets and maybe even more impressively also for five.
Further reading
gplots
Gplots Venn Color
Plots Venn
Various R programming tools for plotting data, including: - calculating and plotting locally smoothed summary function as ('bandplot', 'wapply'), - enhanced versions of standard plots ('barplot2', 'boxplot2', 'heatmap.2', 'smartlegend'), - manipulating colors ('col2hex', 'colorpanel', 'redgreen', 'greenred', 'bluered', 'redblue', 'rich.colors'), - calculating and plotting two-dimensional data summaries ('ci2d', 'hist2d'), - enhanced regression diagnostic plots ('lmplot2', 'residplot'), - formula-enabled interface to 'stats::lowess' function ('lowess'), - displaying textual data in plots ('textplot', 'sinkplot'), - plotting a matrix where each cell contains a dot whose size reflects the relative magnitude of the elements ('balloonplot'), - plotting 'Venn' diagrams ('venn'), - displaying Open-Office style plots ('ooplot'), - plotting multiple data on same region, with separate axes ('overplot'), - plotting means and confidence intervals ('plotCI', 'plotmeans'), - spacing points in an x-y plot so they don't overlap ('space').