---
# System prepended metadata

title: '2021-06-03 <br> HPC6: HPC for Life Sciences'

---

# 2021-06-03 <br> HPC6: HPC for Life Sciences 

Welcome to the hack pad for HPC6, HPC for Life Sciences course from Research Computing at the University of Leeds!

You can edit this document using [Markdown syntax](https://guides.github.com/features/mastering-markdown/).

## Contents

1. [Links to resource](#Links-to-resources)
3. [Agenda Day 1](#Agenda-Day-1)
4. [Agenda Day 2](#Agenda-Day-2)
5. [What's your name and where do you come from?](#What’s-your-name-and-where-do-you-come-from-And-why-do-you-want-to-use-HPC)
7. [Setup instructions](#Setup-instructions)
    5.5. [MacOS/Linux](#MacOS/Linux)
    5.6. [Windows](#Windows)
6. [Code along](#Code-along)
7. [Session 2](#Session-2)
    7.1. [Setup Google Colab](#Setup-your-colab-session)

## Links to resources

- **Contact Research Computing** - https://bit.ly/arc-help
- **Request HPC account** - https://leeds.service-now.com/it?id=sc_cat_item&sys_id=4c002dd70f235f00a82247ece1050ebc
- **Presentation for today** - https://arctraining.github.io/hpc6-life-sciences-2021-06/
- **Github repository** - https://github.com/ARCTraining/hpc6-life-sciences-2021-06
- **Linux command cheatsheet** - https://drive.google.com/file/d/0B4hIpRJzq8DPVG5xdEJWcGlRTkU/view

## Agenda Day 1


| Time     | Agenda                                     |
| -------- | ------------------------------------------ |
| 1300     | Introduction, project and data management           |
| 1350     | Break                                      |
| 1400     | Introduction to the command line           |
| 1450     | Break and Answers                          |
| 1500     | Manipulating files and directories, scripting|
| 1550     | Questions & wrap-up                        |
| 1600     | Close                                      |


## Agenda Day 2


| Time     | Agenda                                     |
| -------- | ------------------------------------------ |
| 1300     | Introduction, using Google Colab, using command line tools           |
| 1350     | Break                                      |
| 1400     | Completing our variant calling notebook           |
| 1450     | Break                           |
| 1500     | Creating a variant calling pipeline and using on ARC4|
| 1550     | Questions & wrap-up                        |
| 1600     | Close                                      |


## What's your name and where do you come from? 

- Darren Newton, oops :) Lecturer in immunology and haematology, interests in NGS sequencing and the time has come to move past galaxy onto HPC
- Alex Coleman, Research Software engineer, my research has previously been in natural language processing and clustering event descriptions data and simulating crime rates using historic data.
- Lauren, 3rd year PhD student from LICAMM
- Jake Leese, PhD student researching evolutionary genetics in arthropods.
- Hannah Rowe, PhD Student, previously worked with bulk RNA-Seq work in Galaxy, however I'm moving onto python and Jupyter notebooks for a new biological dataset.
- Moisés Rojas Rechy, PhD Student, Biological Sciences: Viral glycoprotein interactions.
- Christine Bosch, Lecturer in Food Science & Nutrition, Food bioactives and mechanisms that underpin their health benefits. Dealing with large datasets (microbiome, transcriptomics) increasingly part of our research. 
- James Lloyd, Chemistry PhD student researching a big data approach towards ligand and catalyst design for base metals
- Shannon Jenkins, MSc Precision Medicine student - Researching active microbiome of atherosclerotic plaques (metatranscriptomics)
- Chris Smith, PhD student in antivirulence.
- Michal Zulcinski, 2nd year PhD student, working with RNA-seq and genotyping data (SNPs); using mostly R and Python; hoping to learn more about the HPC to make my anaylses more efficient
- Harry Schofield, PhD student in antimicrobial resistance. 
- Albert Blandy, PhD Student, Biological Sciences, investigating specialised ribosomes in neurodegeneration.
- Sam Turvey - PhD student using computational chemistry for drug design
- Dominique Hirsz, PhD student in plant genetics, working on RNA-Seq datasets and genome analysis
- Becca Chandler Bostock, postdoc in structural virology. Interested in analysing NGS data.  
- Shoaib Ali, PhD student, working with bulk and single cell RNAseq data obtained from GBM tumours.
- Duncan , 1st year PhD student , Microbiology studying the effects of antibiotics on the instestinal microbiome.
- Jessica Edge, 2nd year PhD student in reproductive biology``
- Mohammed Derar, 2nd year Medicine PhD
- Yousef Alghamdi, PhD student , school of Medicine
 
## Setup instructions

For part 1 you will need access to a bash (or bash-like) terminal and a text editor.

### MacOS/Linux
If you have a macOS or Linux machine you're all set! You've already got a built-in Terminal application that we'll be using today.

### Windows
If you've got a Window's machine you'll need to install some software so you're ready to go. 

1. First install Visual Studio Code, a text editor tool from this website - https://code.visualstudio.com/download

    Make sure you select the **User Installer 64-bit**
    ![](https://i.imgur.com/024iei8.png)

2. Install MobaXTerm
![](https://i.imgur.com/qM7ckB4.png)

    1. Navigate using a web browser to https://mobaxterm.mobatek.net/
    2. Select Download 
        ![](https://i.imgur.com/2OWkFeU.png)

    3. Click Download Now for the Home Edition
        ![](https://i.imgur.com/z7snaxu.png)
    4. Select MobaXTerm Home Edition v21.0 (Portable edition)
        ![](https://i.imgur.com/bmdYrg7.png)
    5. This opens a download prompt for a .zip file. Select Save File and click OK
        ![](https://i.imgur.com/jqvN3SW.png)
    6. Go to your Download folder and find the .zip file you have just downloaded
        ![](https://i.imgur.com/C9qIoQ5.png)

    7. Click Extract in the Ribbon Bar and select Extract All
        ![](https://i.imgur.com/lAJtyXq.png)

    8. Using the Wizard window extract the folder at the suggested location
        ![](https://i.imgur.com/rwAEDT2.png)

    9. This should open the extracted folder immediately and allow you to double-click on the MobaXTerm_Personal_21.0 executeable to start the application
        ![](https://i.imgur.com/aYjt8bf.png)

## Code along

### Navigating through the shell:

```bash=
# we can see where we are in the shell by doing 
$ pwd
/home/medacola
```

`pwd` stands for print working directory and will return the full path of our current location.

We can list the contents of our current directory with the `ls` command which lists the contents of the current directory.

```bash=
$ ls
Desktop work junk 
```

We can also get this in a long-form format by adding the options `-l` to `ls`

```bash=
$ ls -l

drwxr-xr-x    1 medacola UsersGrp         0 May 29  2020 Desktop
drw-r--r-x    1 medacola UsersGrp        19 Mar  9  2020 work
drwxr-xr-x    1 medacola UsersGrp         0 Apr 28 14:58 junk
```

We can make folders (also referred to as directories) by using the `mkdir` command:

```bash=
$ mkdir new-folder

$ ls 
Desktop work junk new-folder
```

### Downloading data files

We can download a file from the command line using the command `wget` or web get.

```bash=
$ wget --no-check-certificate https://ndownloader.figshare.com/files/14417834
```

Or you can use `curl` a slightly more modern command

```bash=
$ curl -LOk https://ndownloader.figshare.com/files/14417834
```

We then need to rename it and untar the archive file itself with the commands:

```bash=
$ mv 14417834 shell_data.tar.gz

$ tar -zxvf shell_data.tar.gz
```

### Writing and manipulating text files

Almost all files we come into contact with are text files. We can manipulate these from the command line using programs called text editors.

The most basic text editor, available from the Terminal, is `nano` which you can open from the terminal by doing:

```bash=
$ nano name_of_file
```
Where `name_of_file` is the name of file you want to open. This will open a text editor program in your terminal which looks abit like this:

```bash=
  GNU nano 4.2                        name_of_file




















                                [ Read 0 lines ]
^G Get Help  ^O Write Out ^W Where Is  ^K Cut Text  ^J Justify   ^C Cur Pos
^X Exit      ^R Read File ^\ Replace   ^U Paste Text^T To Spell  ^_ Go To Line
```

We can then type the contents of our file using the cursor and when we want to save use the key combo `CTRL+O`, this will then ask us to confirm the name of the file to save, we press `Enter` to confirm. 

To exit `nano` we use the key combo `CTRL+X` which will return us to the terminal.

We can also use graphical applications like Visual Studio Code:

1. The visual studio code page on opening
![](https://i.imgur.com/13CgVMb.png)
2. To create a new file we click `File` and select `New File` which opens a blank text file we can start editing
![](https://i.imgur.com/JRUVFs7.png)
3. For example adding hello world below
![](https://i.imgur.com/BFR5t8j.png)
4. We can then save our file by opening the `File` menu and selecting `Save`
![](https://i.imgur.com/Sm6J9GA.png)
5. This will then open a folder window where we can specify where we want to save the file

### Examining history and pipes

We can view our previously typed commands in the terminal using the `history` command:

```bash=
$ history

 530  [2021-06-03 14:50:12] ls
  531  [2021-06-03 14:50:18] curl -k https://ndownloader.figshare.com/files/14417834 -L -o shell-data.tar.gz
  532  [2021-06-03 14:50:21] ls -l
  533  [2021-06-03 14:50:23] ls
  534  [2021-06-03 14:50:47] curl -Lk https://ndownloader.figshare.com/files/14417834 -o shell-data.tar.gz
  535  [2021-06-03 14:50:49] ls -l
  536  [2021-06-03 14:50:54] rm shell-data.tar.gz
  537  [2021-06-03 14:50:56] curl -Lk https://ndownloader.figshare.com/files/14417834 -o shell-data.tar.gz
  538  [2021-06-03 14:50:58] ls
  539  [2021-06-03 14:50:59] ls -l
  540  [2021-06-03 14:51:08] wget https://ndownloader.figshare.com/files/14417834
  541  [2021-06-03 14:51:10] ls -l
  542  [2021-06-03 14:59:42] mv 14417834 shell_data.tar.gz
  543  [2021-06-03 14:59:47] tar -zxvf shell_data.tar.gz
  544  [2021-06-03 14:59:49] ls
  545  [2021-06-03 14:59:51] ls -l
  546  [2021-06-03 14:59:57] rm shell-data.tar.gz
  547  [2021-06-03 15:07:18] clear
  548  [2021-06-03 15:07:31] ls
  549  [2021-06-03 15:07:32] cd shell_data
  550  [2021-06-03 15:07:33] ls
  551  [2021-06-03 15:10:43] code .
  552  [2021-06-03 15:26:37] history
```

We can combine two commands in the terminal using the pipe character `|` this means take the output of one command and use it as the input for another command. 

For instance we could combine `history` and `tail` to look at the last 10 entries from `history`.

```bash=
$ history | tail -n 10

  542  [2021-06-03 14:59:42] mv 14417834 shell_data.tar.gz
  543  [2021-06-03 14:59:47] tar -zxvf shell_data.tar.gz
  544  [2021-06-03 14:59:49] ls
  545  [2021-06-03 14:59:51] ls -l
  546  [2021-06-03 14:59:57] rm shell-data.tar.gz
  547  [2021-06-03 15:07:18] clear
  548  [2021-06-03 15:07:31] ls
  549  [2021-06-03 15:07:32] cd shell_data
  550  [2021-06-03 15:07:33] ls
  551  [2021-06-03 15:10:43] code .
  552  [2021-06-03 15:26:37] history
```

Pipes are very useful and can be used to combine lots of powerful commands!

We can also use redirects `>` to redirect the output of a command into a file. Let's say we wanted to save the last 10 commands we used to a file to help document the steps we used.

```bash=
$ history | tail -n 10 > last_10_steps.sh
```

Here we've piped the output of history into tail to get the last 10 items and redirected the output into a shell (.sh) file called last_10_steps.sh.

### Challenge answers with the shell
Following on the from the challenges here (https://datacarpentry.org/wrangling-genomics/01-background/index.html), here are ways to get to the answer with the shell.

Based on the metadata, can you answer the following questions?

1. How many different generations exist in the data?
2. How many rows and how many columns are in this data?
3. How many citrate+ mutants have been recorded in Ara-3?
4. How many hypermutable mutants have been recorded in Ara-3?

Answer 1:

```bash=
$ cut -d, -f 2 Ecoli_metadata_composite.csv | sort | grep -v generation | uniq -c | wc -l
25
```

Answer 2:

```bash=
# to get column number
$ head -n 1 Ecoli_metadata_composite.csv | sed 's/,/\n/g' | wc -l

# to get row number
$ wc -l Ecoli_metadata_composite.csv
63 Ecoli_metadata_composite.csv

```

Answer 3:

```bash=
# first do 
$ cut -d, -f 12 Ecoli_metadata_composite.csv | sort | uniq -c | grep plus
     10 plus
```

Answer 4:

```bash=
# first do 
$ cut -d, -f 6 Ecoli_metadata_composite.csv | sort | uniq -c
      7
      3 Ara-3
     46 None
      1 mutator
      6 plus

# this returns counts of each unique item in column 6, from this we know that mutants are marked with the word `plus`
$ cut -d, -f 6 Ecoli_metadata_composite.csv | sort | uniq -c | grep plus
      6 plus
```

## Session 2

Today's workshop will focus on using Google's interactive python notebooks via [Google Colaboratory](https://colab.research.google.com/).

You will need a google account to use this service but just create one quickly for todays session using [this form](https://accounts.google.com/signup/v2/webcreateaccount?hl=en&flowName=GlifWebSignIn&flowEntry=SignUp).

### Setup your colab session

Once you've logged on to google colab you'll see a screen like this:
![](https://i.imgur.com/9Jkv7y6.png)

From here select the GitHub tab

![](https://i.imgur.com/obJjyxu.png)

In the Enter GitHub Url search box enter `https://github.com/ARCTraining/hpc6-life-sciences-2021-06` and it will populate a list of available notebook files.

![](https://i.imgur.com/ODmhlFI.png)


Click the name of the notebook you want to open and it will open the notebook in a new tab

![](https://i.imgur.com/UatvwmU.png)

