
Introduction To Multi’omics Data Analysis From Microbial Communities (MOMC01R) NOT AVAILABLE
5th May 2025 - 7th May 2025
£300.00
Event Date
Tuesday, August 3rd, 2021
Course Format
This course is not available in a recorded format.
Please email oliverhooker@prstatistics.com to be notified of the next edition.
About This Course
The aim of this course is to provide a thorough introduction to computational approaches for the analysis of multi-omics data from microbial communities with a focus on metagenomic and metatranscriptomic data. We will start from raw sequencing files, introduce different bioinformatic approaches to process sequencing data, followed by multivariate statistical analysis and different visualization techniques. The course will consist of a mixture of lectures and hands-on tutorials. On the last day, participants have the opportunity to bring and analyse their own data or use publicly available datasets.
By the end of the course participants should:
- Be familiar with different workflows involved in the analysis of large-scale multi-omics studies.
- Understand how to generate taxonomic, functional and strain profiles from metagenomic and metatranscriptomic sequencing data.
- Be familiar with applying a multivariate statistical framework to generate hypotheses and account for confounding covariates.
- Be able to use exploratory data visualizations techniques and visualize results from the statistical analysis using R.
Intended Audiences
Course Details
Last Up-Dated – N/A
Duration – Approx. 21 hours
ECT’s – Equal to 2 ECT’s
Language – English
Teaching Format
The course will be held virtually and consists of a mixture of theoretical and practical sessions. Each concept and tool will be first described and explained, followed by a lab session with hands-on experience of applying the tool to provided data sets. At the end of each day there will be additional time for questions. Participants are welcome to bring their own data for the last day.
Assumed quantitative knowledge
Attendees are assumed to have a basic understanding of microbial community studies. The course will not cover data generation aspects (sample collection, library preparation etc) but focus on how to analyse sequencing data starting from raw read files.
Assumed computer background
Familiarity with the command line interface (bash/shell) and R is an advantage. We will offer short introductory labs for both to make the course more accessible to a wider audience. We also encourage attendees to get familiar with zoom prior to the course.
Equipment and software requirements
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations/refunds are accepted as long as the course materials have not been accessed,.
There is a 20% cancellation fee to cover administration and possible bank fess.
If you need to discuss cancelling please contact oliverhooker@prstatistics.com.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Day 1 – approx. 7 hours
Introduction to microbial community analysis
Introduction to the bash/shell
Google cloud setup
QC’ing sequencing data
Taxonomic profiling
Open discussion / questions / wrap-up
Day 2 – approx. 7 hours
Metagenomic Assembly
Functional Profiling
Strain-level Profiling
Multivariate Analysis
Open discussion / questions / wrap-up
Day 3 – approx. 7 hours
Multivariate analysis (continued)
Introduction to R
Metagenomic Data Visualization
Bring your own data
Examples of large-scale multi-omics studies
Open discussion / questions / wrap-up