GeNeo: A Bioinformatics Toolbox for Genomics-Guided Neoepitope Prediction

J Comput Biol. 2023 Apr;30(4):538-551. doi: 10.1089/cmb.2022.0491. Epub 2023 Mar 30.

Abstract

High-throughput DNA and RNA sequencing are revolutionizing precision oncology, enabling personalized therapies such as cancer vaccines designed to target tumor-specific neoepitopes generated by somatic mutations expressed in cancer cells. Identification of these neoepitopes from next-generation sequencing data of clinical samples remains challenging and requires the use of complex bioinformatics pipelines. In this paper, we present GeNeo, a bioinformatics toolbox for genomics-guided neoepitope prediction. GeNeo includes a comprehensive set of tools for somatic variant calling and filtering, variant validation, and neoepitope prediction and filtering. For ease of use, GeNeo tools can be accessed via web-based interfaces deployed on a Galaxy portal publicly accessible at https://neo.engr.uconn.edu/. A virtual machine image for running GeNeo locally is also available to academic users upon request.

Keywords: bioinformatics tools; cancer immunotherapy; neoepitope prediction; somatic variant calling.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Computational Biology
  • Genomics / methods
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Immunotherapy
  • Neoplasms* / genetics
  • Neoplasms* / therapy
  • Precision Medicine