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

Next session, September 2026.

Completed

Long read transcriptomics

In this session, we cover the different long-read sequencing technologies, talk about the pros and cons of each approach, and explore how to process and analyse long-read transcriptomic data.

Shiny: Interactive apps for exploratory data analysis

HiC visualisation

Simple Unix commands to enhance your command line experience

Analysing HTS data with deepTools

Sharing and publishing completely reproducible data analyses

Building reproducible workflows with Snakemake

Fetching published sequencing data from GEO/SRA

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

Resources:

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)

  • Presentation slides
  • 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
    • IGV YouTube Channel

Gene functional enrichment analysis (Jose de las Heras)

Data analysis with R and RStudio

Managing your own software with Conda environments

Running software on the WCB bioinformatics servers

A tour of the WCB bioinformatics servers