A First Look at an Automated Pipeline for NGS-Based Breast-Cancer Diagnosis: The CArDIGAN Approach

Abstract

Continuous improvements on Next-Generation Sequencing approaches are providing a wealth of data for life sciences, and massive application of ICT (Information and Communication Technologies) to molecular research has become essential for the progress of medical research. While several software tools have been developed to assist in analysis, there is still a lack of a focused and integrated solution for several of specific research goals. One such goal is molecular diagnostics of Breast Cancer (BC), the most common malignancy in females. In this paper we present, describe, and evaluate experimentally— on real data—part of a software pipeline we have designed, and are implementing, specifically aimed at assisting in BC diagnostics. The results show that the pipeline is effective in assisting and enhancing BC diagnostics, and encourage towards further automation.