We leverage Reproducible Research, which…

ties specific instructions to data analysis and experimental data so that scholarship can be recreated, better understood and verified. Packages in R for this purpose can be split into groups for: literate programming, package reproducibility, code/data formatting tools, format convertors, and object caching. The primary way that R facilitates reproducible research is using a document that is a combination of content and data analysis code. The Sweave function (in the base R utils package) and the knitr package can be used to blend the subject matter and R code so that a single document defines the content and the analysis.

As a result, we have developed custom workflows and can develop new custom workflows for your research or business needs. A great graphic that illustrates this can be found at the Aberdeen Study Group. We can develop a similar workflow to provide a solution to your data analysis problems!

We can also use RMarkdown to support your publication needs including support with artwork preparation, pre-submission review, journal selection, journal submission, plagiarism check, rapid technical review, and re-submission support.

Other key support includes:
- Ensure that your text, figures, tables, and references are all formatted per the “instructions to author” guidelines.
- Science editing service to address language, structure, overall logic, flow and strength of your research.