Supervisor Sarah Rennie

Project Areas:

1. Data analysis and benchmarking using direct RNA-sequencing datasets for analysing RNA modifications.
2. Testing approaches for charactering editing events at single-cell resolution.
3. Deep learning for RNA modification prediction from RNA sequence.

Current open projects 2025/26 academic year

Reanalysis of public data to learn new biology on post-transcriptional regulation of the virus HPV

• Analysis of HPV viral-epitranscriptome (following up on our recent pre-print https://doi.org/10.1101/2025.07.28.667157)
• Detection of RNA-RBP binding interactions in HPV18 (tonnes of options here =))
• Possibilities for single-cell transcriptomic analyses if interested

Direct RNA sequencing (ONT-DRS) analysis

• New Analysis of our pilot data for detection of non-polyadenylated RNAs using ONT-DRS
• Benchmarking direct RNA-sequencing tools for RNA modification detection in human cell-lines
• Phasing direct RNA-sequencing reads into individual haplotypes to eluicdate allele-specific RNA modifications

Deep learning approaches

• Understanding the effect of negative-selection on learning cis-regulatory principles of RNA modifications or RNA binding proteins

If you are interested in doing a MSc thesis or Bioinformatics project, please send an email to Sarah to arrange a meeting for discussing research interests.

RNA biology course participants interested in joint bioinformatics projects between myself and Peter Brodersen also feel free to reach out and I would be happy to coordinate.