Genetic Data- Digital Droplet PCR
MeSH ID: n/a
Description:
Digital droplet PCR is a digital PCR technique by which a sample is separated into 20,000 water-oil emulsion droplets, where PCR amplification of the target DNA molecule occurs in each droplet. This allows a reading for the concentration of target DNA within each individual droplet, generating a multitude of data points from a single sample.
Best practice for sharing this type of data:
The absolute concentration of target DNA copies per µl of sample should be reported as Tabular data. Tabular data should saved as a .txt or .csv file. The first row(s) should contain information about the dataset, such as the data file name, author, today's date, when the data within the file were last modified, and companion file names. Please also state which symbol has been used to denote missing data (NA is preferred). 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:
Datasets may be added to Extracellular RNA Atlas, ProbeBase, Reference Sequence Database, Genetic Testing Registry, NCBI Genome, NCBI Gene, and Real-Time Quantitative PCR Primer 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.
