mixOmics R Essentials for Biological Data Integration
Sorry you missed this course in 2026. Register your interest below for 2027: Gain essential tools and knowledge to analyse complex biological data.
$1450.00 AUD (inc GST)
What you will learn
Gain contemporary skills and knowledge.
Large biological data, which are often noisy and high-dimensional, have become increasingly prevalent in biology and medicine. To gain a holistic understanding of biological systems, layers of molecular information – or the omics, including transcriptomics, proteomics, metabolomics, metagenomics – must be statistically integrated.
This short course provides the necessary training in statistical data analysis for complex biological data using the renowned integrative analysis R toolkit, package mixOmics.
This course will be useful to researchers at all levels who work with high-throughput omics data, and are seeking the skills to obtain new and deeper insights into biological mechanisms and biomedical problems being faced.
The course is developed and taught by leading researcher, Kim-Anh Lê Cao.
Learn to explore, integrate and interpret data
Be trained in data exploration, integration and interpretation in order to analyse complex biological data. Learn to evaluate the appropriateness of different data integration methods for a given biological question, and interpret the outputs of each method.
Understand key concepts in multivariate methods
Gain an understanding of key concepts underlying multivariate exploratory and integrative methods, and how they can be applied for data analysis.
Learn essential methods for working with large biological data
Gain an overview of statistical and dimension reduction methods for high-throughput biological data. This will help you develop the ability to mine and integrate these large data sets.
Practice using the mixOmics R package
Engage with detailed case studies and an array of methods and hands-on applications with the mixOmics R package. You’ll have an opportunity to select and apply the relevant method to a biological data set, including your own data, honing your critical thinking skills, analytical skills using R, and ability to mine large data sets in practice.
Who you will learn from
Learn from skilled academics and professional experts who will share invaluable knowledge you can use in your job.
Professor Kim-Anh Lê Cao
Professor in Statistical Genomics, School of Mathematics and Statistics
With a background in mathematical engineering, Kim-Anh has had a dynamic career, including as a biostatistician consultant at QFAB Bioinformatics and as a research group leader at the biomedical University of Queensland Diamantina Institute. She is currently Professor at the University of Melbourne, where her research focuses on the development computational and statistical methods for biological data. She leads the mixOmics team with contributors from France, Australia and Canada.
Fees
For Research Higher Degree students enrolled in a University:
$550 AUD (incl. GST)
For Staff and members from Universities & Not-for-profit organisations:
$900 AUD (incl. GST)
Dates
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Course details
This course is ideal for life scientists, and researchers from a wide range of scientific disciplines. Biologists, microbiologists, computational biologists and bioinformaticians who generate and work with high-throughput omics data, as well as research postgraduate students in biomedical and bioscience will find this course useful. Data analysts will also benefit from this course.
To take this course, you should have some familiarity using the R programming language, and a basic understanding of concepts related to statistics.
The mixOmics R Essentials for Biological Data Integration short course is based on an established, and highly successful, face-to-face workshop. You will gain immediately applicable skills and knowledge, including a suite of tools that will help you to analyse complex biological data in the real world.
You’ll also gain skillsets to work at the interface and provide critical collaborative expertise to biologists, bioinformaticians, statisticians, and clinicians.
The mixOmics R package has been developed by Associate Professor Kim-Anh Lê Cao and her team. This ensures you are learning from industry experts who can provide you with deep insights and practical skills.
The course is divided into three modules, covering:
- The basics of multivariate analysis in modern high-throughput biology
- Key computational and analytical aspects of the methods
- Guided case study tutorials for each of the six methods presented.
Throughout the course, you will be given an opportunity to interact with Kim-Anh through weekly live Q&A sessions.
By the end of this course, you’ll be able to:
- Explain the concepts of biological data integration
- Evaluate the appropriateness of a data integration method for a given biological question
- Apply the relevant method to a biological data set
- Interpret the outputs of each method, including assessing the performance of the method.
Other key skills covered include:
- Analytical skills using R
- Analysis of complex biological data
- Critical thinking in statistical analysis
- Ability to mine large data sets
- Knowledge on how to statistically integrate biological data sets.
This short course runs over four weeks. Your time commitment is approximately 40 hours of online study.
There is no formal assessment, however participants will engage in formative quizzes and a final peer-reviewed assignments that will give you the opportunity to analyse your own data, or other data provided.