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I am interested to know what programs people use to plot CpG methylation data to create those pretty visuals you find in publications. I don't have any issues doing the analysis and identifying differential methylated sites and regions. However, I would like to be able to plot the average methylation of groups/samples across a chromosome. It seems that some type of smoothing is necessary because if you just plot all the points and connect them it is way to dense to plot with any program I can find. I am aware there is a program called BSSmooth but I really don't need to re-analyze my data, only plot it. I have searched and searched and just cannot find a program that was meant for this type of thing. A lot of people seem to use circos plot programs in R but I cannot figure those things out and I have yet to find any kind of tutorial on plotting methylation. I know it seems unimportant because it's really the differential methylation stats you want, but my boss always wants to "see" what the methylation looks like. Maybe people are just writing there own scripts using R. I am not at all good with plotting in R but can follow a tutorial. I have WGBS data and targeted BS data sets I would like to be able to visualize. Any suggestions would be greatly appreciated.
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Have you looked at deepTools (https://deeptools.readthedocs.io/en/develop/ )?
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...06-18-2026, 07:11 AM -
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM
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