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data_type:genetic_data:dna_methylation

Genetic Data- DNA Methylation

MeSH ID: D019175

Description:
Addition of methyl groups to DNA. DNA methyltransferases (DNA methylases) perform this reaction using S-ADENOSYLMETHIONINE as the methyl group donor.

Best practice for sharing this type of data:
Raw sequence outputs may be stored as .fastq files. Following analysis, DNA methylation profiles may be presented along with relevant information regarding the sample such as cell or tissue type, phenotypic data about the donor, sample status (case vs control) etc. and presented as a Feature Table: Features should be shared at the lowest level collected (eg sequence variants, OTU), such that combining into higher level categories (eg genus/phylum) can be repeated if desired. Metadata should include information about what variant calling protocol was used (eg DADA2) and what database was used to find labels for the variants (eg Greengenes). Ideally, the read count data would be accompanied by any other experimental, environmental, clinical, or demographic data needed to recreate the analyses in the manuscript. If these are included as a separate data table, then it is vital that the ID codes for the samples can be linked to ID codes for sample level data. If the study involves human data, then ethical considerations around sharing need to be evaluated: Subject Data Table (Tabular data). Column headings should describe the content of each column and contain only numbers, letters, and underscores – no spaces, or special characters. Lowercase letters are preferred. Row names should be consistent with those used in the article and in other related datasets.

Most suitable repositories:
DNA methylation data may be added to ArrayExpress, DNA Methylation Interactive Visualization Database, ENCODE Project, Encyclopedia of DNA Elements at USCS, EWAS Data Hub, Methbank, mirDNMR, Restriction enzymes and methylases database, and SoyBean Knowledge Database.

Best practice for indicating re-use of existing data:
For public datasets please provide a DOI or other stable identified for the dataset itself *and* include a citation for the dataset in the reference list. Be sure to indicate exactly which data has been re-used, particularly when multiple versions of the dataset exist. In many cases, this is best achieved by sharing the code used to extract the part of the data that you analyzed. In some cases it may be best to share the exact dataset(s) you analyzed as well.

For access-controlled data authors should provide a link to instructions for obtaining access (e.g. here is the information page for ADNI (Alzheimer's Disease Neuroimaging Initiative): http://adni.loni.usc.edu/data-samples/access-data/).

When re-using a private dataset from a previous study please contact the data owners to discuss how the data can be made public.

Most suitable repositories:
Not applicable

data_type/genetic_data/dna_methylation.txt · Last modified: 2021/04/23 18:46 by samantha