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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Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...-
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Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...-
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