Source Code for Biology and Medicine is accepting submissions for its new R/Bioconductor section, edited by Section Editor Dr. Levi Waldron at City University of New York, along with our Editors-in-Chief. This section will showcase well-documented and usable software packages, workflows, and data resources. It is not required that the scientific approach implemented by the software or data resource be novel, but rather that the implementation is novel and likely to help others in the field.
Submission types include
- packages/libraries: should be well-documented and include an evaluated "vignette" that explains and provides examples of typical uses. Packages should be hosted by CRAN or Bioconductor, or an equivalent third-party repository that checks packages for cross-platform operability. Note that this requirement is not met by posting packages on an author-hosted website, Bitbucket, or Github.
- data resources: provide either well-described novel datasets in a well-documented and open format, or provide a more usable version of public data through standardization, curation, or documentation.
- workflows: implement a series of reproducible steps required for an analysis, potentially spanning multiple R/Bioconductor libraries and even multiple programming languages. Workflows must provide example data so they are readily reproducible, and be adaptable to new analyses.
Source Code for Biology and Medicine promotes reproducibility in science by recognizing the extra work required for data analysis that is not only repeatable, but adaptable to other uses and improvements in methods. Works are expected to be published under one of the free licenses listed at http://www.gnu.org/licenses/license-list.en.html.