PAMOGK-Web: a framework for cancer subtype identification using copy number variatıons

Abstract

Detection of molecular sub-groups of cancer is important for developing cancer therapeutics and to understand the underlying causes of the molecular differences in these groups. The cancer sequencing projects made multi-omics data available for large cancer cohorts. The multi-omics data provides multiple views into the cancer which can be used to find underlying causes from different perspectives and capture relations not possible with a single view approach. Previously, we developed a pipeline that uses multi-omics data to detect sub-groups of patients called PAMOGK. PAMOGK forms multiple views of the patients using pathways and multi-omics data and assess patient similarities under these views. PAMOGK was designed as a general framework that can be used to map many different omics data but was experimented with mutation, transcriptome, and proteome. In this work, we extend the use of PAMOGK with copy number variation data which shows comparable results to experiments without it. As a second contribution, we provide a web framework designed for PAMOGK easier to make it accessible to general users: PAMOGK-Web. This new web based framework is able to abstract the PAMOGK pipeline and provide a simple interface to run experiments and return results to the users. PAMOGK-Web will be using the generic design of PAMOGK to provide ready to use experiments that include setups using different omics data.