# Duke HTS Course Tutorial - Introduction to Computing for HTS Experiments¶

## Course Components¶

In this course, you will learn how to generate and analyze RNAseq data. Roughly, we have the following components:

• Experimental Design and Statistics How do we design experiments so that results are easily interpretable and answer the question(s) we are interested in.

• Analysis of Data How do we properly analyze experimental data, so that results are correct.

• Computational Procedure Analysis pipeline (Bioinformatics)

Finally, we want to do all of the above in a REPRODUCIBLE fashion.

The analysis pipeline has several different apps. Some are written in R, and so require knowledge of the R programming language (minimal - but some proficiency is needed). Some have components in python, and some are binaries. Both of these last types of applications require moderate proficiency in the 'bash shell' or 'unix command line'. Therefore, we will cover the following topics:

• Basic R
• Basic Unix/Linux commands

Additionally, we will use the bootcamp to reinforce the statistical lecture materials by walking you through some of the examples using R, and we will cover some 'data visualization' techniques that include graphics in R.

All of this will be done within the Jupyter notebook tool, which allows for what is called 'literate programming' and reproducible pipelines.

## How this is all setup¶

Detailed instructions will follow, but here is a summary of what is to be done for clarity.

### Materials¶

The course materials are archived in a for download via git. They are also available here as a compressed archive file. If you are a git user, clone the repo using:

### Start the image running¶

\$ docker run --name hts-course -v YOUR_DIRECTORY_WITH_COURSE_MATERIAL:/home/jovyan/work \ -d -p 127.0.0.1\:9999\:8888 \ -e PASSWORD="YOUR_CHOSEN_NOTEBOOK_PASSWORD" \ -e NB_UID=1000 \ -t dukehtscourse/jupyter-hts-2019

### Run the notebooks¶

Open a browser window on your computer and go to the address https://<your server url>:8888