Developing statistical frameworks for analysing next generation sequencing data

Developing statistical frameworks for analysing next generation sequencing data

Project details

Advanced sequencing technologies continue to revolutionise biological research. RNA-seq, ChIP-seq, ATAC-seq, CUT&Tag and bisulfite-seq have been widely used for studying gene/transcript expression, epigenetics regulation and DNA methylation. Many methods and software tools have been developed in the past (McCarthy, NAR 2012 40:4288-4297; Chen, F1000Research 2017 6:2055). However, there is still room for improvement.

This project will focus on developing and improving statistical frameworks for sequencing data analysis. Depending on the interests of the student, the project can be tailored to cover a few topics including: 

  1. Differential transcript or exon usage analysis with RNA-seq 
  2. Differential DNA methylation analysis with bisulfite-seq/enzymatic methyl-seq  
  3. Benchmarking different methods and software tools

About our research group

The Chen lab's research focuses on gene or transcript expression, alternative splicing, DNA methylation, single-cell omics and spatial technologies. We develop statistical bioinformatics methodologies and software tools to make sense of different types of sequencing data and to answer biological questions of interest.

We are a small but enthusiastic and motivated bioinformatics team, embedded in a top-class research division in cancer biology and stem cells. Through daily collaboration, you will be working at the forefront of cancer research with world-leading experts in the fields. You will have access to very exciting biological data generated by the latest cutting-edge sequencing technologies and develop novel methods to make groundbreaking discoveries in cancer research. 


Email supervisors



Dr Yunshun Chen

Dr Yunshun Chen
Laboratory Head

Project Type: