Improvements on pathwaymapper: a collaborative pathway curation tool

Abstract

Information visualization focuses on visually representing abstract data to amplify human cognition. Graph visualization is one of the most common types in the eld of information visualization because of its capabilities to present huge amount of data in a clear and meaningful manner. A graph is a suitable data structure for representing relational information and for this reason graph visualization has a wide usage in biological pathway visualization as well. In this thesis, we focus on collaborative construction of cancer pathways and visualization of cancer genomics data overlaid over such networks. Several biological pathway visualization tools have been developed to help biologists analyze cancer genomics data, using various formats, including standard formats like SBGN, in the past. Nevertheless, most biologists prefer curated pathway diagrams like the ones featured in The Cancer Genome Atlas (TCGA) manuscripts, using a simpler notation. These pathway diagrams outline the alterations occurring in pathways for di erent cancer types. To address this need, a web-based tool called PathwayMapper was previously developed. PathwayMapper can be used to view pre-curated cancer pathways or to create new pathways from scratch. It has many features including overlay of genomic alteration data from the cBioPortal. It also includes a collaborative mode so that the users can interactively create and modify the cancer pathways. With this thesis, we improve PathwayMapper in several ways to make it a more complete and powerful editor with a better user interface. New features include complexity management operations, edge bend support, interactive node resize, and various highlighting capabilities. Furthermore, the user interface has been improved to be more user friendly with the addition of a toolbar.