Analysis pipeline for genome methylation experiments
Nowadays, high-throughput sequencing technologies are widely utilized in the biomedical research field. It is easy to generate tons of genome sequencing datasets from various experiments such as ChIP-seq, RNA-seq, whole genome/exome sequencing, and DNA methylation sequencing. However, it is very challenging to analyse the large datasets from various high throughput genome experiments. In this bioinformatics master project, we intend to build a data analysis pipeline for genome data sets obtained from whole genome methylation sequencing experiments. The analysis pipeline should enable biologists to analyse the methylation data themselves. Ideally, the pipeline shall be built in Python with a user friendly interface or as a simple command line tool. So far, we already have a set of prototype MATLAB scripts that can be used to analyse methylation sequencing data. The prospective bioinformatics master student will mainly focus on adapting, modifying, and improving our existing MATLAB scripts, to transform them into a user-friendly computational toolbox such as a Python package. The student will learn advanced genome analysis, data mining, software/computer package development and big data analysis. The person trained from this master project will become an attractive candidate as data scientist in both research and industry in the future. The project will be carried out in collaboration with scientists at Oslo University Hospital.
Research Group: Biomedical informatics (BMI)
Supervisors: Junbai Wang, Magnar Bjørås (Oslo University Hospital) and Torbjørn Rognes (internal)