Welcome to BIS180L

Instructor: Julin Maloof jnmaloof@ucdavis.edu

Teaching Assistant: Bryshal Moore brymoore@ucdavis.edu

The goal of this course is to introduce you to the tools and thinking required for bioinformatics analysis.

This is a computer-based class. No bench work.

At the end of this course you should be able to:

• Use cloud computing resources like Jetstream and AWS
• Navigate the Linux operating system at the command line for file management and invocation of bioinformatics programs
• Automate repetitive computational tasks using loops
• Write scripts in R for data analysis and display
• Perform genome wide association studies (GWAS)
• Analyze Illumina sequencing data to find sequence polymorphisms

• Perform a genome Assembly
• Tentative: Find methylated regions of the genome
• Analyze RNA-seq data to find differentially expressed genes and pathways
• Make and deploy Shiny web applications
• Reconstruct genetic co-expression networks
• Analyze metagenomics data
• Apply best practices for reproducible data analyses via git version control and markdown notebooks
• Use Agentic AI tools to help with coding

• This class will require a lot of work outside of lab hours.
• But you will gain a solid foundation in bioinformatic analysis, focused on second-generation sequencing data.

• Both R and Linux have command-line interfaces
• Antiquated?
• NO! Written code provides flexibility, creativity, and power not available in any other way
• Linux (or Unix / Mac)
  • Outstanding built-in tools for data crunching
  • Provides access to hundreds of bioinformatics programs
  • Easy to automate repetitive tasks

• R
  • Powerful scripting, statistical, data processing, and graphical capabilities
  • Many bioinformatics packages are developed in R
  • Easy to automate repetitive tasks.

• AI is rapidly changing the way people code
• Currently it is still important to understand what AI generated code is doing and how it works
• Especially true in data analysis applications (how do you trust the output?)
• You want to use AI to speed up your coding but not replace your thinking

• You ARE allowed to use AI tools
• You are NOT allowed to directly paste any text/question/code into any query/search/AI engine
• You are encouraged to solve the problems on your own without AI…you will learn better
• There will be a written/in-class portion of both exams that does not allow usage of AI
• I plan to have an AI module later in the class to show how to use agentic tools (going beyond pasting things in to ChatGPT).
  • need to determine what to cut out!

Secrets for success:

1. You are learning a new language, treat it as such.
2. Go slow. If your goal is to get out of this room as soon as possible you will not succeed.
3. Read the lab instructions carefully. See #2.
4. Do not cut and paste code. Type it; you will learn it better.
5. Take the time to understand a command. THINK!
6. Do ask for help when you are stuck or confused.
7. Be kind to yourself and your community.

• 45% Lab assignments
• 25% Midterm (In class May 01, Take Home Available May 01, Due May 07, 1:10 PM)
• 25% Final (In Class June 10 3:30, Take Home Available June 07, Due June 09, 5:00 PM)
• 5% Playposit lecture quizzes + possible discussion Qs + Attendance

Developing code is an interactive process. Both your friends and the web can be excellent resources.

However Any direct copying of text or code from any person (in this class or on the web, etc) is considered plagiarism in the context of this course. Okay to use AI generated code–give attribution.

If you receive inspiration or ideas from an external source give attribution

• Main website: http://jnmaloof.github.io/BIS180L_web/

  • Lab instructions
  • Course Schedule
  • Helpful Links (to be updated as we go)
  • Reading assignments (to be updated as we go)

• Canvas

  • Gradebook

1. Clear documentation
2. Reproducible results
3. Informative names (files, variables, functions)
4. Logical organization
5. Documents/Data in open (non-proprietary) formats
   • This is essential for achieving 1 and 2

1. Get a virtual linux machine running
2. Clone Assignment 01 repo into Rstudio
3. Practice Markdown
4. Learn a little Linux command line

• The computer lab machines run Windows
• Bioinformatics on a Windows machine is painful (although getting better) (R is fine)
• Solution: virtual machine!
• Use Jetstream2 to run a virtual Linux machine in the cloud as part of the NSF-funded Access-CI
• You can connect to your virtual machine from any computer, including your laptop or home computer

• Universities have many very large computers (a.k.a. servers) in various places around the country
• These servers can be split up to be many separate “virtual” machines, each emulating an individual computer
• You can connect to these virtual machines and it just like having your own computer, but it is in the “cloud”
• Terminology:
  • Each virtual machine is an instance of a machine image.
  • You can think of the image as a snapshot (or template) of a machine that captures the OS, the installed programs, etc.
    
  • The image that you are using is called BIS180L and was created by John Davis and myself for this class.

• There are two ways to connect to your instance:

1. Using a Virtual Network Connection (VNC). This allows the graphical display of the instance to be displayed on your local computer
2. Using a secure shell (SSH). This provides a text connection to your instance. An advantage for slow internet connections.

• You can also transfer files from your instance to other computers using SFTP (Secure File Transfer Protocol)

Quick demo of VNC and SSH

As detailed in the lab notes for today:

• We have created a virtual machine instance for each of you
• The first lab section details how to connect.

• Can you use your own computer to connect to your Virtual Machine?
  • Yes, this is easy and you will probably want to, to make it easy to work outside of class
  • But for today, please first connect using the lab PCs
  • Also eduroam is slow, so if everyone is in here on their own laptop on wifi, things won't work very well
• Can you use your own computer to run the analyses directly?
  • For R/Rstudio analyses, probably (But make sure your R is up to date!)
  • For Linux/Possibly, if you are running a Mac or Linux machine. The first lab manual links to install notes for the Linux machine. I have a similar, although out-of-date document for Mac.
  • We will NOT provide troubleshooting help for your own computer (other than helping you connect it to the VM)

1. Get a virtual linux machine running
2. Clone Assignment 01 repo into Rstudio
3. Practice Markdown
4. Learn a little Linux command line

Markdown is a text-based formatting system for quickly and easily generating nicely formatted output.

This presentation as well as the entire BIS180L website was written in markdown.

It helps achieve three guiding principles:

1. Clear documentation
2. Reproducibility
3. Open formats

1. Get a virtual linux machine running
2. Clone Assignment 01 repo into Rstudio
3. Practice Markdown
4. Learn a little Linux command line

We will work through a tutorial developed by Ian Korf.

You are learning a new language; treat it as such.

• Keep notes
• Be patient
• Practice and repetition help
• It will get easier

• Instead of clicking on an icon, typing a command
  • command [options] [file-path]
• directory structure

• Assignments will be turned in via github
• There will be a separate repo for each assignment
• Detailed instructions are given on the lab page for today
• We can help if you get stuck
• For today's lab you will need to turn in four files (two markdown files and their correspongind .html counterparts).
• Due before class on Tuesday, but there will be new material this Thursday

• If you took BIS 15L you are probably familiar with using Github Desktop
• Github Desktop is installed on the instances and you can use it
• Alternatively you can interact with Git directly in Rstudio. This my personal preference.
• I'll demo this later in this period once people get going.

Slack is our main tool for communication (other than lecture and one-on-one lab time).

There are two UC Davis Slack channels that I have added you to:

• bis180l-student-announcements-2026
  • Posting on this channel should be limited to me or John, although you can reply to posts with follow-up questions
• bis180l-student-help-2026
  • This is the place to seek help. If you are confused or stuck someone else is as well.
  • If you know the answer to a question please contribute

• Be kind and respectful to each other
• Remember that we all come from different backgrounds
• Promote questions and discussion
• Think about how your Slack posts could be viewed by others