Methylation plotter

A dynamic Web tool for easy methylation data visualization



Methylation plotter allows to generate publication-ready, high quality graphics summarizing methylation data in lollipop- and heatmap-like plots. Some descriptive stats and comparisons are provided.

Please cite our paper Methylation plotter: a web tool for dynamic visualization of DNA methylation data Source Code for Biology and Medicine 2014, 9:11.

Further information, including example datasets, is available at the documentation webpage.

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Methylation data

Methylation file must be a tab separated file with the following structure:
  • Methylation levels must be indicated in percentage (from 0 to 1).
  • Each row contains the methylation levels for a sample. The last row must indicate the position of the CpGs (positions can be unsorted).
  • First column indicates the sample identifier. Each middle column contains the methylation levels for a CpG.
  • Last column indicates at which group (i.e., control, treatment) do the sample belongs.
Mind that the maximum number of both CpGs and samples to be plotted is 100. A toy dataset is available here.

Interval file is an optional, tab separated file indicating the intervals of methylation for the gray scale color legend. A toy dataset is available here . If not provided, a predefined set of ten intervals ranging from black (fully methylated CpGs) to white (fully unmethylated CpGs) corresponds to unmethylated CpGs will be used.

Plotting options

There are two major plot types:
  • circles offers a lollipop-style plot. Each CpG is represented by a circle filled with a shade of gray according to its methylation status. Missing data are represented by crosses. By default the lollipop-syle plot takes into account the distance between CpGs (the longer the distance between them, the longer space between lollipops); this behaviour is included as the proportional circles option. The nonproportional circles disables this behaviour, just spacing the CpGs regardless of the actual position.
  • grid represents methylation data in a heatmap-like manner. Missing data are represented in blue. This does not take into account the distance between CpGs that's why it is more useful when plotting a large number of CpGs.


There are four ways to sort the data:
  • as-is plots data in the same order as it was in the input file.
  • by methylation level sorts data by the mean of the samples from more methylated to more unmethylated.
  • by group sorts data using the group column of the input file alphabetically.
  • unsupervised clustering sorts data implementing an unsupervised clustering analysis.

Methylation plot size

The height and width sliders allow the fine tuning of the final plot size.
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© IMPPC, 2014 - Designed and maintained by Izaskun Mallona and Anna Díez-Villanueva. Logo by Julien Douet.