Cancer Data Visualisation

Visualisation of patients suffering from certain types of cancer with related gene expression data.

• Overview : We want to visualise a group of data points representing patients and controls having a certain type of cancer, based on their personal characteristics as well as gene expression data. The visualisation will involve a novel distance metric to calculate clusters based on the research by Rachel Jeitziner (whom we met in class) of the Swiss Institute of Cancer Research. Based on this, we can create clusters of patients. Also, we aim to allow the user to select different features like age/subtype of cancer/ethnicity/sex and visualise the patients in the clusters according to the said features. We also plan to connect this group with another visualisation of genes (which is available publicly) and make a map from the patients to the possible genetic reasons of their disease.

• Motivation : Sometimes clinics might find it easier to visualise the huge amount of data available and make targeted genetic treatments easier for patients in places where technology and resources are limited.

• Target audience : Clinics, researchers, maybe even patients.

• Related work : Research by Rachel.

• Inspiration : The importance of cancer research. People should die in proper times.