* Name some limitations of using bash scripts for doing reproducible data analysis? * Name some limitations of using tools with graphical user interfaces (GUIs) for doing reproducible data analysis?
#Weirdest spss code series
Now join me in opening the slides for today's tutorial which you can find within the Reproducible Research Tutorial Series at the website. I'll be discussing R although again I don't expect you to know much about R for this tutorial. Here you have various options for tools that you can use, many people will use R or Python. In today's tutorial, we'll be discussing some of the best practices for analyzing your process data using a scripting language. This is the place your sequence data should be deposited before you submit your manuscript. In addition, in Mothur we have a command called make.sra which has been a game changer in terms of helping people to post their sequence data to NCBI's Sequence Read Archive, also called the SRA. We've really gone out of our way to make Mothur a great tool for encouraging reproducible analyses. Similarly, our wiki has all past versions of the SILVA, RDP, and Greengenes databases that will work well with Mothur. If you go to the Mothur GitHub repository, you can get any version of Mothur you want and it's a self-contained executable. These dependencies can be really difficult to track down, this is frequently called dependency hell for those trying to reproduce someone else's analysis. Other tools for analyzing 16S rRNA gene sequence data are out there but they tend to require a lot of other dependencies. If you'd never use Mothur before, you should definitely check it out. In that tutorial, we used Mothur to process the raw sequence data to generate files that we'll be using in this and future lessons. It took a little effort but it's great to see how we could accidentally burn our project to the ground and with the help of Git and Bash, we're able to rebuild it with minimal further input from us.
#Weirdest spss code how to
I hope you're able to make it through the last tutorial in which we discussed how to use a single Bash script to automate our analysis. Welcome back to the Riffomonas Reproducible Research Tutorial Series.
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