TSNAD v2.0: A one-stop software solution for tumor-specific neoantigen detection

Zhan Zhou; Jingcheng Wu; Jianan Ren; Wenfan Chen; Wenyi Zhao; Xun Gu; Ying Chi; Qiaojun He; Bo Yang; Jian Wu; Shuqing Chen

Computational and Structural Biotechnology Journal (Jan 2021)

TSNAD v2.0: A one-stop software solution for tumor-specific neoantigen detection

Zhan Zhou,
Jingcheng Wu,
Jianan Ren,
Wenfan Chen,
Wenyi Zhao,
Xun Gu,
Ying Chi,
Qiaojun He,
Bo Yang,
Jian Wu,
Shuqing Chen

Affiliations

Zhan Zhou: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou 310018, China; Corresponding authors at: College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China (Z. Zhou, S. Chen). College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China (J. Wu).
Jingcheng Wu: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Collaborative Innovation Center of Artificial Intelligence by MOE and Zhejiang Provincial Government, College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
Jianan Ren: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
Wenfan Chen: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Polytechnic Institute, Zhejiang University, Hangzhou 310015, China
Wenyi Zhao: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Collaborative Innovation Center of Artificial Intelligence by MOE and Zhejiang Provincial Government, College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
Xun Gu: Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
Ying Chi: Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare, Alibaba DAMO Academy, Hangzhou 311121, China
Qiaojun He: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou 310018, China
Bo Yang: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou 310018, China
Jian Wu: Collaborative Innovation Center of Artificial Intelligence by MOE and Zhejiang Provincial Government, College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China; Innovation Institute for Artificial Intelligence in Medicine, Zhejiang University, Hangzhou 310018, China; Real Doctor AI Research Centre, School of Medicine, Zhejiang University, Hangzhou 310058, China; Corresponding authors at: College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China (Z. Zhou, S. Chen). College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China (J. Wu).
Shuqing Chen: Zhejiang Provincial Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China; Corresponding authors at: College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China (Z. Zhou, S. Chen). College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China (J. Wu).

Journal volume & issue: Vol. 19
pp. 4510 – 4516

Abstract

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TSNAD is a one-stop software solution for predicting neoantigens from the whole genome/exome sequencing data of tumor-normal pairs. Here we present TSNAD v2.0 which provides several new features such as the function of RNA-Seq analysis including gene expression and gene fusion analysis, the support of different versions of the reference genome. Most importantly, we replace the NetMHCpan with DeepHLApan we developed previously, which considers both the binding between peptide and major histocompatibility complex (MHC) and the immunogenicity of the presented peptide-MHC complex (pMHC). TSNAD v2.0 achieves good performamce on a standard dataset. For better usage, we provide the Docker version and the web service of TSNAD v2.0. The source code of TSNAD v2.0 is freely available at https://github.com/jiujiezz/tsnad. And the web service of TSNAD v2.0 is available at http://biopharm.zju.edu.cn/tsnad/.

Published in Computational and Structural Biotechnology Journal

ISSN: 2001-0370 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Technology: Chemical technology: Biotechnology
Website: https://www.journals.elsevier.com/computational-and-structural-biotechnology-journal

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