BC3203

Subject Handbook for BM3331: Mastering Big Genomic Data and BC5203: Advanced Bioinformatics

Lecturers

Ira Cooke (ira.cooke@jcu.edu.au) : Metagenomics, RNASeq
Roger Huerlimann (ROGER.HUERLIMANN@OIST.JP) : Metagenomics
Matt Field (matt.field@jcu.edu.au) : Genomic Variants
Ulf Schmitz (ulf.schmitz@jcu.edu.au) : Networks and Functional Enrichment
Siyuan Wu (thaddeus.wu@jcu.edu.au) : Networks and Functional Enrichment

Lecture and Tutorial Times

Always refer to the official JCU timetable at https://timetable.jcu.edu.au for the most up to date timetable information. In this subject you will learn through a combination of online lectures, and live computer workshops.

Each week new lecture content will be added to LearnJCU for you to review. On Mondays at 1pm we will have a four hour computer workshop session. These computer workshops are crucially important because they will allow you to work on the assignments while having access to tutors for one-on-one advice.

Activity Scheduled Time Location
View Lectures Regularly. Your choice LearnJCU
Computer workshop Mondays 1pm-5pm 300-001;

Assessment

This subject places a strong emphasis on practical skills. These are assessed through coding assignments (available as part of weekly tutorial sessions) and through your major assignments.

The process of accessing, completing and submitting these assignments follows a best practice workflow for doing reproducible bioinformatics research. Assistance with this process is available during practical sessions. We have also prepared this guide for reference in case you forget one of the steps.

Coding Assignments

These are released weekly and will be assessed as a single assessment item based on the portfolio of work across all assignments. You should aim to spend a few hours on each of these and complete roughly one per week. Skills you learn in these assignments will be used for your major assignment (see below).

Tutorial Week Released Guide Github Classrooms Link Expected Outputs
Unix Fundamentals 1 Week 1 TBA TBA  
Unix Fundamentals 2 Week 1 TBA TBA  
R Fundamentals Week 2 TBA TBA  
Tidyverse 1 Week 3 TBA TBA TBA
Tidyverse 2 Week 4 TBA TBA TBA
Genomic Features and Alignments Week 6 TBA TBA TBA

To see a full list of all your assignment repositories, login to github and then visit the following link

http://github.com/JCUBioinformatics

Major Assignment

Both BM3331 and BC5203 have a single major assignment. Details of this will be released in week 4 and will differ depending on the subject you are enrolled in.

Learning Resources

Analysis workflows

In lectures we cover analyses of three major types of sequencing data.

  1. 16S amplicon data for Metagenomics
  2. RNAseq data for gene expression analysis
  3. DNA sequencing data for genetic analyses

To help you learn each of these we have prepared the following guides. These are practical workflows that you can work through at your own pace. They are not assessable directly but material from these will appear on the exam.

Workflow Guide
Metagenomics TBA
RNA-Seq TBA
Variants TBA

Coding lectures

Each week you will see two types of lectures appear in the relevant module on learnJCU. Standard lectures cover theoretical concepts. “Coding” lectures cover important programming concepts or command line tools that should form the core of your analysis toolbox. You are encouraged to follow along when doing coding lectures. The links below provide relevant data and commands to run to help you follow coding lectures.

Lecture Topic Link
Coding Lecture 1 Intro to Unix TBA
Coding Lecture 2 Working with NGS Data (FastQC) TBA
Coding Lecture 3 Intro to R TBA
Coding Lecture 4 Tidyverse & QIIME TBA
Coding Lecture 5 Tidyverse 2 & QIIME TBA
Coding Lecture 6 Genomic Features TBA

Beginner tutorials and resources

  1. Command Line: Throughout this subject you will build familiarity with the unix command line and with programming (using R). If you haven’t encountered these previously, we strongly recommend you complete this interactive tutorial introduces the unix command line.

  2. R and the Tidyverse: The recommended textbook for the R components of the subject is R for Data Science by Garrett Grolemund, Mine Cetinka-Rundel and Hadley Wickham. The entire book is available for free online at https://r4ds.hadley.nz/

Computational Resources

To complete the tutorials and assignments for this subject you will need access to a computer with a unix-like command line interface. To make sure everyone has access to the same environment we have setup an RStudio web server with everything you need.

This is available at https://rstudio.bioinformatics.guide .

You will receive an email from the subject coordinator with a username and password to access this service.

Note: Web based rstudio seems to work best using the google chrome browser.

If you are willing to put in some effort you can set up everything on your own personal computer. This is relatively easy on macOS or Linux but is also possible (with some effort) on windows. If you choose to do this you will need to be fairly self sufficient as your instructors will not have time to troubleshoot installation issues.

Please see this guide for setting things up on your own computer.

AI Assistant

RStudio includes a built-in AI Assistant that can chat with you, explain code and help you debug. It is not switched on by default – you need to connect it to an AI provider first.

You are free to choose whichever provider you like. There are several free options (Google Gemini, OpenRouter) as well as paid ones, and if you have a GitHub Student Developer Pack you can also enable GitHub Copilot for inline code completion.

Please see this guide for step-by-step setup instructions.

A note on using AI in this subject: the assistant is a learning tool, not a substitute for understanding. You are responsible for everything you submit, so make sure you can explain any code you hand in. Be careful about what you paste into a free service – prompts sent to free-tier models may be used for training, so don’t paste assessable work or anything private.

Cheat Sheets

In this subject you will regularly encounter new commands or functions. Cheat sheets help you to remember commands you know and can sometimes also help you discover new commands or functionality you weren’t aware of.

We recommend you download the cheat sheets below. If you find them useful you may want to print them out and bring them along to tutorial sessions.

Guides for common tasks

If a guide is missing or you have a question not covered please email the subject coordinator to request it.

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