High-performance bioinformatic analysis of gene editing targets using Python Standard Libraries

Overview

The CRISPR-Cas9 technology allows the modification of virtually any gene in any organism of interest. It has generated a lot of interest, both in the research community and the general population.

One of the crucial components of CRISPR experiments is the design of the 'guide RNAs' that will control where modifications occur. It is vital that the modification is made efficiently and at the desired location. This calls for bioinformatic approaches to design these guide RNAs.

Our existing Python-based bioinformatic pipeline is capable of scaling to large datasets, however, there remains opportunities to further reduce its run-time. This project entails the application of parallel computing to reduce the overall run-time of the pipeline.

Research activities

This project will require you to apply your computer science skills in order to improve upon the existing method.

A starting point could be to consider the multiprocessing capability of Python, via its standard libraries.

Outcomes

In this project, you will review literature and existing bioinformatics pipeline in order to gain an understanding of what is currently available.

You will have the opportunity to write multiprocess code in the Python programming language in order to fully utilise the computers hardware. During this, you will gain experience in working with a bioinformatics pipeline and have the opportunity to work alongside researchers working in the expanding field of bioinformatics.

Skills and experience

This project requires you to have strong programming skills. Some experience with low-level programming languages, such as C or C++, and writing multithreaded code would be beneficial but not required.

No prior experience with biology is necessary, but you must be willing to learn relevant concepts.

Keywords

• bioinformatics
• gene editing
• CRISPR
• high-performance computing

Contact

Contact the supervisor for more information.