Learning objectives

After this lesson, participants will

• Be able to describe Python and provide rationale for using it
• Know how to start a Jupyter Lab session on Biowulf (Jupyter Lab will be used to interact with Python throughout this course)
• Be familiar with places for getting Python packages
• Become familiar with navigating the Jupyter Lab environment
• Be able to describe Python command syntax
• Know how to find help for Python commands
• Become familiar with continuing and self-learning resources

What is Python and why use it?

• Scripting language
  • Facilitates reuse and reproducibility
• Can be used to analyze large datasets
• Extensive external packages that can be used for
  • Data wrangling
  • Data visualization
  • Single cell RNA sequencing analysis
  • Working with biological sequences
  • Interfacing with bioinformatics databases
• Strong support community
• Easy to learn
• Python packages can be found at see the Python Package Index

Signing onto Biowulf

In this course series, participants will interact with Python through Jupyter Lab on Biowulf. Thus, the first step is to sign onto Biowulf using ssh. Replace username with participant's own Biowulf username.

• Mac: use ssh through the Terminal
• Windows: use ssh through the command prompt

Change into Biowulf data directory

Use cd to change into the participant's data directory on Biowulf. Again, replace username with participant's Biowulf username.

Request an interactive session

Request an interactive session using sinteractive with the following options.

• --gres=lscratch:5: to allocate 5gb of local temporary/scratch storage space
• --mem=2gb: to request 2gb of memory or RAM
• --tunnel: to open up a channel of communication between local machine and Biowulf to allow interaction with applications like Jupyter Lab

Complete the tunneling process

Load Jupyter

After the tunnel has been created, go back to the Biowulf interactive session and activate Jupyter.

Start Jupyter Lab

Use the command below to start a Jupyter Lab session.

Users will be provided with three URLs (example below) and they can copy and paste either one into a web browser to interact with Jupyter Lab.

Warning
The URLs change with each Jupyter Lab session, so please do not copy from the examples shown below. Copy from the URLs provided in the Biowulf interactive session terminal instead.

Jupyter Lab - file explorer and launcher

• File explorer
• Launcher for starting language specific notebooks (for this course series, choose the python/3.10 notebook)

Jupyter Notebook - cells

Python education resources

• Coursera
• Dataquest

Visit the self learning resources page to request a Dataquest or Coursera license.

Coursera recommendations

• Programming for Everybody (Getting Started with Python)
  • Instructor: Charles Severance, PhD (University of Michigan)
• Data Analysis with Python
  • Instructor: IBM staff
  • Includes data wrangling and regression analysis
• Data Visualization with Python
  • Intructor: IBM staff
  • Introduces data visualization using packages such as Matplotlib and Seaborn

Dataquest recommendations

• https://www.dataquest.io/course/introduction-to-python/
• https://www.dataquest.io/path/data-scientist/
• https://www.dataquest.io/path/data-analyst/

Python command syntax

The command syntax for Python is composed of the

• Command
• Argument, which is enclosed in the parentheses and what the command will act on
• Options, which is enclosed in parentheses and alters the way the command runs

Example of a Python command with and without options

Include option sep to place a comma between "Hello" and "welcome to Python".

Finding help for Python commands

The help command can be used to view documentations for Python commands. It follows the Python command syntax. Insert the command in which help is needed into the parentheses.

Example of using help

Copy class data to data directory

The example datasets used for this course series reside in /data/classes/BTEP/pies_2023_data. Make a copy in your data directory.