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setup.Rmd
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---
title: "Course Setup"
author: "Mark Dunning"
date: "February 2020"
output:
html_notebook:
toc: yes
toc_float: yes
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Course Setup for Day 1
In this course we will demonstrate how to run some standard analysis tools for RNA-seq data. The majority of Bioinformatics tools are built with a *command-line* environment in mind, rather than Windows or Mac OSX. To simplify the installation of these tools, we are providing some resources on the *cloud* that you can log into for the duration of the course.
## 1. Create an account at InstanceHub
*InstanceHub* is a tool created at The University of Sheffield for creating cloud resources for computing practicals. You will need to go to [instancehub.com](instancehub.com) and create an account. **Make sure that you specify the same email address that you signed-up to the course**.
## 2. Launch the Lab
Choose the menu option *View my labs* on the left-hand menu. The lab **Introduction to the Command Line for Bioinformatics** should be visible. Click the *Participate* button.
## 3. Connect to the lab
Press the *Start Lab* (green) button and wait whilst the lab loads...
Once *Start Lab* has been replaced by *Disconnect*, the *Connection Information* tab will be updated with an IP address etc.
Enter the following address in your web browser
Replacing **IP_ADDRESS** with the numbers next to **Instance IP** in the *Connection Information* box.
```
http://IP_ADDRESS:6080
```
e.g.
```
http://3.8.149.23:6080
```
**Do not click Disconnect**
## 4. Open a termninal window
You should be presented with a unix desktop environment that we can use to learn about the command-line and tools for processing RNA-seq data.
To open a *Terminal* (in order to enter Unix commands), there is a "Start menu" in the bottom-left corner from which you can select *System Tools* and then *LXTerminal*
## 5. Change user
Finally, in order to follow the materials we need to change the user that we logged in as from `root` to `dcuser`.
Type the command into the terminal window **exactly** as it appears below
```
su - dcuser
```
# Setup on your own machine
Both Mac OSX and Windows 10 have the ability to run some of the commands presented in this course to navigate around a file system, copy files and list directories. However, you may prefer to practice in a "safe" environment, such as that used during the workshop. Furthermore, the NGS tools presented may be difficult to install.
You can launch the same computing environment on your own machine using a tool called *Docker*.
Docker is an open platform for developers to build and ship applications, whether on laptops, servers in a data center, or the cloud.
- Or, it is a (relatively) painless way for you to install and try out Bioinformatics software.
- You can think of it as an isolated environment inside your exising operating system where you can install and run software without messing with the main OS
+ Really useful for testing software
+ Clear benefits for working reproducibly
- Instead of just distributing the code used for a paper, you can effectively share the computer you did the analysis on
- For those of you that have used Virtual Machines, it is a similar concept
## Installing Docker
### Mac
- [Mac OSX - 10.10.3 or newer](https://www.docker.com/docker-mac)
- [Older Macs](https://download.docker.com/mac/stable/DockerToolbox.pkg)
### Windows
- [Windows 10 Professional](https://www.docker.com/docker-windows)
- [Other Windows](https://download.docker.com/win/stable/DockerToolbox.exe)
Once you have installed Docker using the insructions above, you can open a terminal (Mac) or command prompt (Windows) and type the following to run the Day 1 environment
```
docker run --rm -p 6080:80 markdunning/rnaseq-toolbox
```
Entering the address in your web browser should display the environment
```
http://localhost:6080
```
### Using the environment to analyse your own data
With the default settings, the computing environment is isolated from your own laptop; we can neither bring files that we create back to our own OS, or analyse our own data.
However, adding an `-v` argument allows certain folders on your own OS to be visible within the enviroment.
Assuming the files I want to analyse are to be found in the folder `PATH_TO_FASTQ`, the following command would map that directory to the folder `/home/dcuser/rnaseq_data`
```
docker run --rm -p 6080:80 -v /PATH_TO_FASTQ/:/home/dcuser/rnaseq_data markdunning/rnaseq-toolbox
```
At the terminal, we should be able to see our files with the `ls` command
```
ls /home/dcuser/rnaseq_data
```
### Analysis on the UoS cluster
As described above, `docker` can be used to run the environment presented in this course on a personal laptop. However, there are some security implications of docker that prohibits it being installed on a high-performance computing system. An alternative is `singularity`, which allows computing environments to be distributed as a single image file. We have created such a singularity image and made it available on sharc (The University of Sheffield's HPC).
Firstly, login to sharc in the usual manner and then open an interactive shell.
```{bash eval=FALSE}
qrsh
```
The singularity image is available at the following location:-
```{bash eval=FALSE}
ls /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif
```
**The commands presented in the Introduction to Shell section (e.g. `ls`, `cd`, `pwd`...) are already available when you first login to `sharc`**. However, the tools specific to NGS analysis will require you to add the path to the singularity image before the command.
For example, to run `fastqc` you can navigate to your directory containing your fastq files with the usual `cd` command.
```{bash eval=FALSE}
cd /path/to/your/fastq/files
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif fastqc *.fastq.gz
```
Other commands that require you to list give the path to the singularity image are as follows:-
```{bash eval=FALSE}
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif multiqc
```
```{bash eval=FALSE}
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif hisat2-build
```
```{bash eval=FALSE}
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif hisat2
```
```{bash eval=FALSE}
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif samtools
```
```{bash eval=FALSE}
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif featureCounts
```
```{bash eval=FALSE}
singularity exec /shared/bioinformatics_core1/Shared/software/singularity/command_line_20200212.sif salmon
```