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# EvoHull Bioinformatics & Reproducible Metabarcoding Course This project contains the resources for the EvoHull course on reproducible metabarcoding to be held September 12-14 2016. #evohull2016 [@evohull][1] All these teaching resources are free, open, and public domain ![CC0][2] Sometimes is is easier to open the [Google docs folder][3] directly, rather than the OSF panel displaying it in-line. The live GDocs [course manual][4] is also here. We are going to organise this course using the [OSF][5], and you should familiarise yourself with this site. There are good [OSF guides][6] and [YouTube videos][7] (eg [getting started with OSF][8] video 2 mins). ### ELN **You will need to keep a Electronic Laboratory Notebook (ELN) of all your work.** A detailed wriiten record is essential for all research scientists, not only to demonstrate what you did to others, but also because it will make your research life *much* easier going forward. **You will do this ELN in the wiki.** Read the [wiki guide][9] first, then explore the wiki by just clicking, doing stuff, and seeing what happens. I have written [some guides to creating an ELN][10] using the wiki which might also be useful. You will each have a notebook in the ELN component. ### Workshop Manual Teaching in this course will follow a detailed and interactive [course manual][11]. This is a google doc, its "live" so we may add extra explanations as we go along if something isn't clear. It might be useful to have this open in a tab throughout. ### Computer Environment You will be working on the EvoHull bioinformatics machines running Ubuntu, with all the appropriate software installed. We may also make use of [VIPER][12], the University of Hull's impressive High Performace Computer grid. Some students also bring a laptop or tablet for less formal compute needs, and use the Ubuntu machine for the analyses. It is fine if you do or don't wish to bring your own machine, both work. ### Example Data and Analysis Scripts You will be provided with extensive sample data. This is sequence data generated in EvoHull, some will be nice and clean, others horribly dirty real-world data. We will teach you how to deal with both. Data is kept in the [GitHub repository for the course][13] along with analysis scripts. ### Reading material We have included a component of reading materials, papers, to help support your learning. At the moment this is very incomplete and will be improved as we go through the course. Don't forget though that you can contribute to the course by adding materials yourself if you think we should have it here! [1]: [2]: [3]: [4]: [5]: [6]: [7]: [8]: [9]: [10]: [11]: [12]: [13]:
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