Supporting data for "CandiMeth: Powerful yet simple visualization and quantification of DNA methylation at candidate genes"

Dataset type: Software, Workflow, Epigenomic, Bioinformatics
Data released on May 20, 2020

Thursby S; Lobo DK; McNulty H; Pentieva K; Zhang S; Irwin RE; Walsh CP (2020): Supporting data for "CandiMeth: Powerful yet simple visualization and quantification of DNA methylation at candidate genes" GigaScience Database.


DNA methylation microarrays are widely used in clinical epigenetics and are often processed using R packages like ChAMP or RnBeads by trained bioinformaticians. However, looking at specific genes requires bespoke coding which wet-lab biologists or clinicians are not trained for. This leads to high demands on bioinformaticians, who in turn may lack insight into the specific biological problem. We therefore wished to develop a tool for mapping and quantification of methylation differences at candidate genomic features of interest, without using coding, to bridge this gap.
We generated the workflow CandiMeth (CANDIdate METHylation) in the web-based environment Galaxy. CandiMeth takes as input any table listing differences in methylation generated by either of the popular R-based packages above and maps these to the human genome. A simple interface then allows the user to query the data using lists of gene names. CandiMeth generates 1)Tracks in the popular UCSC genome browser with an intuitive visual indicator of where differences in methylation occur between samples, or groups of samples 2) Tables containing quantitative data on the candidate regions, allowing interpretation of significance. In addition to genes and promoters, CandiMeth can analyse methylation differences at LINEs and SINEs. Cross-comparison to other open-resource genomic data at UCSC facilitates interpretation of the biological significance of the data and the design of wet lab assays to further explore methylation changes and their consequences for the candidate genes.
CandiMeth (RRID:SCR_017974; Biotools:CandiMeth) allows rapid, quantitative analysis of methylation at user-specified features without the need for coding and is freely available, with extensive guidance, at CandiMeth GitHub repo.

File NameSample IDData TypeFile FormatSizeRelease Date 
GitHub archivearchive3.01 MB2020-05-03
readmeTEXT3.76 KB2020-05-03
Tabular DataCSV102.54 MB2020-05-03
Tabular DataCSV0.35 KB2020-05-03
Tabular DataCSV1.99 KB2020-05-03
Tabular DataCSV1.99 KB2020-05-03
Tabular DataCSV146.06 MB2020-05-03
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Funding body Awardee Award ID Comments
Economic and Social Research Council CP Walsh ES/N000323/1 EpiFASSTT grant
Biotechnology and Biological Sciences Research Council K Pentieva and CP Walsh BB/S020330/1 HDHL EpiBrain award
Medical Research Council CP Walsh MR/J007773/1
Date Action
May 20, 2020 Dataset publish
June 8, 2020 File Supp.Table3__mean_beta_D8_Track.csv updated
June 8, 2020 File Supp.Table3__mean_beta_WT_of_D8.csv updated
June 18, 2020 Manuscript Link added : 10.1093/gigascience/giaa066