Moving on

If you made this far, congratulations! Learning any programming language takes a big effort.

This is only the beginning. You will probably need more R knowledge, both generalized and specialized, to accomplish your research goals. Here are a few resources to develop stronger data science skills in R.

• Data Science in a Box is a online course by Mine Çetinkaya-Rundel with videos for further development of R skills.
• R 4 Data Science by Hadley Wickham and Garret Grolemund is a comprehensive book providing guidance on leveraging R for data science aims
• What They Forgot to Teach you about R (and workshop version) describes some meta processes for ensuring a repeatable workflow.
• orginal R manuals (highly technical)

There are many other resources to help develop skills in genetics, bioinformatics, geospatial analysis, Bayesian statistics, ….you name it. Look for the resources that will help you develop skills in R. One very reliable place to start are CRAN Task Views which provide a list of packages and other relevant R resources specific for a given topic such as environmetrics (ecology), spatial tools and agriculture.

Another good source for keeping up with major developments in R, contributed R packages and other R resources is R Weekly which puts out a weekly blog post (also available in a weekly podcast and an RSS feed).