To promote reproducibility, WRA expects researchers to identify and cite data sets
and/or code used in their experiments and studies. These may be large or complex
data sets that can include, but are not limited to, data from microarray, genomic,
structural, proteomic, or video imaging analyses. Authors should cite both the data
set repository and the published article in which the data set and/or code was originally
described. Citations of data should be included in the reference list with persistent
unique identifiers (e.g., active DOIs, accession numbers, etc.). If computer code
or software was created to generate results or interpret data, then a statement
to that effect should be included in the “Data availability” paragraph. In cases
where the software is publicly available, the URL of the software informational
page should be provided. It is preferred that authors use established, publicly
available data type-specific repositories. If there is no appropriate repository
available, general publicly available repositories should be used (e.g., Dryad,
figshare, etc.).
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