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GNOMEViewer : visualisateur interactif de mutations somatiques

Translated title of the thesis: GNOMEViewer : interactive somatic mutation vizualiser
  • Beatriz Kanzki

Student thesis: Master's thesisMaster in Engineering: Engineering

Abstract

Next Generation Sequencing (NGS) techniques now provide new opportunities for oncogenomics researchers. These techniques are very useful and provide access to crucial information for research by detecting and quickly identifying possible genetic mutations to diagnose diseases or improve treatments. In order to use them effectively, it is essential that each researcher has the ability to process, explore and interpret this large amount of data carefully and quickly. Oncology research is progressing rapidly. New knowledge and new results are continually generated through large-scale collaborative projects that provide open access to clinical and genomic cancer data. Unfortunately, few researchers can use this information to its full potential even if it is publicly available. The growing size and complexity of data generated by NGS technologies and the number of public heterogeneous databases available to researchers make the analysis and exploration of information a great challenge for the typical researcher. This applied research report presents the design decisions, functionalities, structure, and data conversion process demonstrated in a software prototype named GNOMEViewer, which specializes in the visualization of somatic cancer-related mutations. The software prototype aims to facilitate the visualization of complex data for oncology researchers. The objective of this research is to show that this, easy to use user interface design, enables cancer researchers to seamlessly compare their patient’s data against publicly available databases. GNOMEViewer was designed using Spark, Parquet, and the University of Berkeley’s Berkeley Genomics Format (ADAM) that are all open source Big Data technologies, which can easily scale on demand in the cloud. Our hope is that GNOMEViewer becomes the future reference tool for the visualization of somatic mutations for oncology researchers.
Date28 Jan 2019
Original languageFrench
Awarding Institution
  • École de technologie supérieure
SupervisorAlain April (Supervisor)

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