After several hours of hard work and learning new stuff in R Markdown, I was able to release an (first!) Rmarkdown research report in html where I describe in details all steps for reproducing the analysis performed in a recent article published in Plant Pathology (Lehner et al. 2016. Plant Pathol. In the article, two relationships were studied: soybean white mold (Sclerotinia sclerotiorum) incidence (inc, %) and soybean yield (yld, kg/ha) and incidence and sclerotia weight (scl, g/ha). The data were obtained from a scientific report on fungicide efficacy evaluated in 35 trials conducted across several locations and 4-year period in Brazil.
My motivation to produce this report was to demonstrate, using R programming, all steps of my analysis, from data preparation to presentation of data and results, which can be reproduced either by future myself or other people interested in the same topic. Instead of giving away all the data and my (messy!) original code, I thought that investing time to prepare a tutorial-like report could contribute to popularize the use of meta-analysis in plant pathology.
All data, codes, pre-print version of the article and supplementary materials were also made available at this GitHub repository. The report is the html output of an R Markdown file prepared with the R Studio IDE for R. The plots were prepared using both the base R graphics and ggplot2, whichever was more convenient. Most of them are simple versions for a quick visualization, not actually formatted for final publishing.