Project details

Long-read sequencing provides researchers with a powerful tool for studying transcriptome architecture. This project will explore the complex splicing patterns that occur in tissue samples by combining spatial omics methods with short- and long-read sequencing technology. Building upon our previous work (Tian et al. Genome Biology 2021 22:310), the project will involve the analysis of cutting-edge data generated for protocol benchmarking and to study healthy and diseased tissue. This work will lead to the development of free, open-source software distributed to researchers worldwide via the Bioconductor project. 

We are looking for a student with a strong statistical or computational background (e.g. an undergraduate degree in statistics and mathematics), programming skills, an interest in biology and a desire to develop their skills in genomic data science.

About our research group

The Ritchie laboratory develops analysis methods and open-source software that are tailored to new applications of genomic technology in biomedical research. Our major interests include: 

• statistical methods for modelling variation in RNA-sequencing data 
• software for interactive visualisation of gene expression data 
• software for the analysis of single-cell and long-read gene expression and methylation data 
• applying our data analysis skills to study epigenetic and genetic regulation in development and cancer together with our collaborators.