We’re excited to offer a comprehensive and highly rated training programme in collaboration with John Cole (Glasgow Bioinformatics Core), designed to equip wet-lab immunologists, clinical scientists and other life scientists with the skills and confidence to carry out their own bioinformatic data analysis.
Bioinformatics is becoming increasingly essential across the life sciences. As omic technologies become more widely used to complement wet-lab research in immunology, understanding how to design, analyse and interpret these datasets is now a valuable skill for researchers at every stage of their career.
Effective and affordable training in this area can be difficult to find, which is why we offer flexible, expert-led bioinformatics training designed specifically for wet-lab life scientists, with discounted rates available for all BSI members.
All courses are available as either live online teaching or flexible self-paced learning, allowing you to choose the learning style that best fits around your research and workload.
Is this training for you?
Our courses are designed for lab-based scientists who:
- Are planning or carrying out sequencing, mass-spec or spatial omics experiments
- Want to learn bioinformatics and R to support their research or career development
- Need to better understand omics data in the scientific literature
- Are looking for practical skills and confidence applying bioinformatics to real datasets
By joining this top-rated training programme, you’ll gain:
- Flexible live and self-paced learning designed to fit around your research schedule
- Practical skills in R, omics analysis and data visualisation
- Confidence analysing your own or public datasets
- Career-enhancing skills to strengthen your CV
- Ongoing support from experienced bioinformaticians
- Affordable training, with discounted rates for BSI members
Which course is right for me?
Our entry course ‘Omic data analysis and visualisation using R’ is essential for complete beginners, covering the foundations of bioinformatics, R-coding and omic data visualisation. Additionally, we have optional extra courses depending on need, which build on specific lessons obtained in the first course. They allow for specialisation into advanced topics.
| Omic data analysis & visualisation using R | Further omics, statistics and clinical data in R* | Single cell & spatial omics** | Essential command line omics & genome analysis* | |
|---|---|---|---|---|
| Bulk RNA-seq | ESSENTIAL | USEFUL | ||
| GeoMx | ESSENTIAL | ESSENTIAL | ||
| Proteomics | ESSENTIAL | USEFUL | ||
| Metabolomics | ESSENTIAL | USEFUL | ||
| Genomics | ESSENTIAL | ESSENTIAL | ||
| Epigenomics | ESSENTIAL | ESSENTIAL | ||
| Single-cell RNA-sq | ESSENTIAL | USEFUL | ESSENTIAL | |
| Single-cell spatial | ESSENTIAL | USEFUL | ESSENTIAL |
*This course is aimed at those who have carried out the entry-level course ‘Omics, bioinformatics & R for biologists’ or have a comparable level of experience.
**This course is aimed at those who have a basic familiarity with R.
Omic data analysis and visualisation using R
Course details
Designed for wet-lab scientists, this top-rated course is essential for complete beginners and covers:
- Theory of library preparation, sequencing and data processing for bulk, single cell and spatial omics
- Introduction to R and Rstudio, how to handle data in R
- Extensive theory and practical computer sessions in omic data analysis using R
- Lessons on making beautiful plots using R, e.g. PCA, heatmap, violin, MA, volcano, gene-set enrichment, gene ontologies, pathway analysis, and more
- Providing all the tools needed for you to do your own analysis of any omic dataset
Who signs up for this training?
Wet-lab scientists…
- With little or no previous experience in bioinformatics
- Doing or planning on doing an omic experiment as part of a project
- Keen to learn R and bioinformatics to advance their career, for example after finishing a PhD or in future post-docs
- Who need to understand omics in the current literature
- Who’ve been on a course but are missing the practical skills and confidence to put it to use
Further omics, statistics and clinical data in R
Course details
Designed for wet-lab scientists, this top-rated course is an advanced course designed for wet-lab immunologists, biologists and other life scientists who have some experience (for example, have completed our beginners 'Omic data analysis and visualisation using R' course) and want to learn about:
- Exploring clinical data using R. Summary statistics, P-values, linear models, survival curves, correlation, PCA
- Identifying confounding covariates and correcting for batch effects
- Generating differential expression tables for RNA and Proteomic datasets
- Writing your own functions in R - a time-saving superpower
- Power calculations for grant bids
- Deeply exploring omic datasets with >2 groups. Using biomarker, overlap & signature analysis, and identifying novel groups using K-means clustering
Alongside the core content, you’ll also build experience in:
- The Linux environment and command-line coding
- Sequence alignment using BLAST, Bowtie2, Kallisto and Cell Ranger
- QC of sequence data
- ChIP-seq and ATAC-seq
- RNA-seq data alignment
- Identifying polymorphism and mutation
- Generating and visualising phylogenetic trees
- Writing pipelines
- Data structures in R
- The TidyVerse and R markdown
Who signs up for this training?
Wet-lab scientists…
- Who have completed our entry level course ‘Omics, bioinformatics & R for biologists’ or have comparable experience
- Keen to further develop their knowledge and skills into more advanced analysis
- Who are thinking of doing omic experiments throughout their career and would like the skills to be wholly independent
- Who need to understand omics in the current literature
Essential command line bioinformatics
Course details
The course is designed for wet-lab immunologists, biologists and other life scientists who have some experience, covering Linux and the command line, plus all of the typical tools and pipelines used in command-line omics, particularly genomics. This includes:
- The Linux environment and command-line coding
- Sequence alignment using BLAST, Bowtie2 and Kallisto
- QC of sequence data
- Writing pipelines
- How to call polymorphisms and mutations, and visualising them in R (circos, oncoplot)
- Generating and visualising phylogenetic trees
- ChIP-seq and ATAC-seq
- RNA-seq alignment
Who signs up for this training?
Wet-lab scientists…
- Who have attended the first course ‘Omic data analysis and visualisation using R’ or have a comparable level of experience
- Doing or planning on doing an omic experiment as part of a project
- Planning to analyse omic datasets regularly throughout their future career
- Exploring or planning to explore their own genomic or epigenomic datasets
- Keen to learn R and bioinformatics to advance their career, for example after finishing a PhD or in future post-docs
- Who need to understand omics in the current literature
Single cell and spatial omics
Course details
Designed for wet-lab scientists, this top-rated course is an advanced course designed for wet-lab immunologists, biologists and other life scientists who have a basic familiarity with R and want to learn about:
- The theory behind widely used single cell and spatial RNA technologies
- The Seurat package and objects
- QC, doublet removal, PCA, UMAP, clustering, cell identification, cell frequencies
- Handling replicates using integration
- Differential expression and pseudo-bulk
- Putative ligand / receptor interactions
- Trajectory analysis
- CITE-seq / antibody capture
- Visualisation and exploration, sub setting and re-clustering
- CytAssist (Visium HD), CosMx and Xenium spatial analysis
- Spatial niches, custom regions and molecules
Who signs up for this training?
Wet-lab scientists…
- Who have a basic familiarity with R and RStudio, or have completed our entry level course ‘Omics, bioinformatics & R for biologists’
- Who are thinking of doing single cell or spatial analysis
- Keen to further develop their knowledge and skills into this cutting edge field
- Who need to understand omics in the current literature
Choose your bioinformatics training journey
- Choose your learning format: live online or self-paced
- Pick a bundle or course
- Start learning
Access the same expert-led content, practical training and career-ready skills, with the flexibility to learn when it suits you. Study at your own pace, revisit lessons whenever needed, and build practical bioinformatics skills with ongoing support throughout.
Join expert-led online teaching with structured sessions, live interaction and the opportunity to ask questions in real time. Ideal for learners who prefer guided teaching, scheduled learning and direct support from experienced bioinformaticians.
Meet the trainer
What makes these courses different? We caught up with trainer John Cole to discuss how the programme was designed for wet-lab scientists, why so many researchers find bioinformatics intimidating at first, and how the courses help build real confidence in coding and omics analysis.
Read the full interview with John Cole.
What do previous attendees think?
The course has had over 3,000 attendees since 2019, with a mean rating of 9.5/10 for content and delivery, and 94% of participants were happy with the session length and pace.
“Great course! Never thought that something so complex like R could be explained in such clear and simple manner.”
“The content of the course was great and was clearly relevant to biological data analysis from start to finish. I really appreciate that each line of code and each function within the code was explained, as this has left me able to write and customise my code and plots in hundreds of ways.”
“Really enjoyed this outstanding course – allowed a complete novice (me) to become R-functional – I will continue to improve as the course tutorial structure/course materials make it easy to revise/hone skills.”
“I've been on other R courses and this was the best by far as I actually finished it feeling a lot less scared of R and omics generally!”
"I think the course was excellent. I had very little knowledge of bioinformatics at all, and I now feel I have a firm understanding of the different aspects of sequencing, data presentation and what said presentation shows."
“I have done 3 R courses, this is the only one that actually gives me joy. Thanks so much!”
“Fantastic course, really helpful lots of personalised support. Couldn't recommend more”
“Excellent course and John's explanations of complex concepts was superb. Would definitely recommend to others.”
“Despite John saying it really is for beginners I was convinced that I would really struggle based on my lack of experience, but I did soooooo much better than I thought. John has an amazing way of breaking it down to really manageable chunks pitched just right for beginners but answering deeper questions for those more experienced. I would recommend this course to anyone and everyone.”
“I have followed other R courses in the past and this was the only one delivered in a way that wet lab - only scientists can comprehend R. I found very insightful the way each line of code was explained and the discussion over the basics of every visualisation tool. I certainly feel that I am equipped with the skills and most importantly the confidence to use R for my data analysis. Thank you!”
“Excellent course on omics data analysis with hands-on coding exercises. Five star experience. Highly recommended!”
“This is probably the most useful course I have ever attended”
“Great course, thanks for everything - makes me not only more confident in working with omic data myself, but also in assessing papers and presentations on the topic. Best course I've done for years!”
