Bioinformatics Live
Bioinformatics Live is our series of demonstrations focusing on specific applications of bioinformatics, data analysis and programming. The aim of these sessions is to share knowledge, develop skills and create a network of computational biologists.
You can find the schedule below as well as links to previous talks. We are always keen to have new speakers so please get in touch if you are interested!
Upcoming
Coming soon in 2026.
Completed
Shiny: Interactive apps for exploratory data analysis
GeneTonic RNA-seq Shiny App
Shiny app deployment:
HiC visualisation
A brief overview of available tools for visualising HiC data.
The pros and cons of different tools both for genome wide exploration and plotting at specific viewpoints.
HiGlass vs Juicebox for Genome wide heatmaps
- What are the differences?
Plotting with HiCExplorer and Cooltools
Simple Unix commands to enhance your command line experience:
Input dataset and shell script: https://bifx-core3.bio.ed.ac.uk/Shaun/Shaun/training/unix_tutorial/
Ensembl Biomart: https://www.ensembl.org/info/data/biomart/index.html
Notes on regular expressions: https://www.datacamp.com/cheat-sheet/regular-expresso
Analysing HTS data with deepTools
ProfilePlyr: Importing deepTools objects into R
Example deepTools shell script
Example profilePlyr R script
Building reproducible workflows with Snakemake
Introduction to workflow languages
Why should I write workflows instead of bash scripts
Snakemake workflows and rules
Rule parameters and wildcards
Running a workflow: Outputs and dry runs
Snakemake tutorial: https://snakemake.readthedocs.io/en/stable/tutorial/tutorial.html
Fetching published sequencing data from GEO/SRA
Searching and exploring SRA (the Sequence Read Archive) https://www.ncbi.nlm.nih.gov/sra
Searching published datasets in GEO (Gene Expression Omnibus) https://www.ncbi.nlm.nih.gov/geo/
Downloading sequence files with sra-tools https://github.com/ncbi/sra-tools
SRA explorer tool https://sra-explorer.info/
ENA (European Nucleotide Archive) https://www.ebi.ac.uk/ena/
A tour of the Ensembl website and databases
The Ensembl genome database is an online resource for genomic annotation, tools and visualisation:
Genome assemblies for 300+ species
Gene and transcript annotations
- Gene/transcript centric data e.g. expression, proteins, homologues, variants
Variation, regulation and comparative genomics data
Analysis tools such as BLAST and the Variant Effect Predictor
Data downloads via FTP, BioMart portal and programming APIs for R/Python/Perl
Interactive genome browser
VIDEO: Quick guide to Ensembl
TUTORIAL: Ensembl training course
Analysing CUT&RUN sequencing data (Kashyap Chhatbar)
CUT&RUN (Skene et al. 2017) is a method to analyse protein interactions with DNA. Unlike ChIP, which fragments and solubilizes total chromatin, CUT&RUN is performed in situ, allowing for both quantitative high-resolution chromatin mapping and probing of the local chromatin environment. Analysis steps are like ChIP-seq with a few additional steps. The talk will cover accelerated analysis using NextFlow CUT&RUN pipeline to automate some of the steps below:
Mapping sequencing reads to host and spike-in genomes
Calculate normalization factor and generate spike-in normalized genome browser tracks for visualisation
Analyse fragments by size
Peak calling using sparse enrichment analysis algorithm SEACR (Meers et al. 2019)
Generate summary plots and heatmaps
Genome browsers (IGV demonstration)
Overview of commonly used genome browsers
- Websites, servers, programming tools, desktop applications
IGV demo
Loading data and genomes
Navigating the genome
Customising the display
Working with HTS files - bigWig, BAM, VCF, RNA-seq data
Gene functional enrichment analysis (Jose de las Heras)
Data analysis with R and RStudio
Creating projects in RStudio
Using git in RStudio to version control scripts and software
Using Renv to manage package versions in a project
Using RMarkdown to annotate and publish your analysis
The usethis() package in R is particularly useful for managing github within RStudio
Managing your own software with Conda environments
How to install Conda on a server or your own computer
The difference between Anaconda and Miniconda
How to find and install software available via Conda
How to manage software environments for different projects in Conda
How to run different versions of the same package
Sharing environments with other researchers
Running software on the WCB bioinformatics servers
Introduction to different types of software on the bioinformatics servers
Running bioinformatics software via the command line
Checking which bioinformatics tools are available
Running specific versions of bioinformatics tools for reproducible research
Accessing web-based tools hosted on the bioinformatics servers
Options for managing your own software environment
A tour of the WCB bioinformatics servers
Introduction to the bioinformatics core facility and where to find help
Connecting to the bioinformatics servers (SSH and SSH keys)
Navigating the file system (home spaces, group spaces, genome reference data etc.)
Making files available on the web (/homes/www)
Monitoring running jobs (htop and ps commands)
Logging out without losing your session (tmux terminal multiplier)