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D3Oncoprint: Standalone software to visualize and dynamically explore annotated genomic mutation files

Wednesday, September 13, 2017 — Poster Session II

3:30 p.m. – 5:00 p.m.
FAES Terrace
NCI
GEN-3

Authors

  • A Palmisano
  • Y Zhao
  • RM Simon

Abstract

Advances in Next-Generation Sequencing technologies have led to a reduction in sequencing costs, allowing many laboratories to obtain more genomic datasets easily. Sequencing data require effective analysis tools to use genomic data for biologic discovery and patient management. Available software packages typically require advanced programming knowledge, system administration privileges or they are web services that force researchers to work on outside servers. With the goal to support the interactive exploration of genomic datasets on local machines with no programming skills required, we developed D3Oncoprint, a standalone application to visualize and dynamically explore annotated genomic mutation files. D3Oncoprint provides links to curated variants lists (e.g., CIViC, My Cancer Genome, and FDA approved drugs) to facilitate the use of genomic data for biomedical discovery. D3Oncoprint also includes curated gene lists from BioCarta pathways, and FoundationOne cancer panels to explore commonly investigated biological processes. This software provides a flexible environment to dynamically explore one or more variant mutation profiles provided as input. The focus on interactive visualization with biological and medical annotation significantly lowers the barriers between complex genomic data and biomedical investigators. D3Oncoprint can help researchers explore their own data, without the need of an extensive computational background. D3Oncoprint is free software for non-commercial use. It is available for download from the website of the Biometric Research Program (BRP) of the Division of Cancer Treatment and Diagnosis, NCI (https://brb.nci.nih.gov/d3oncoprint/). We believe that this tool will empower researchers to translate the information from the collected data sets to biological insights and clinical applications.

Category: Genetics and Genomics