research data . Dataset . 2019

pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

Zhou, Chi; Wei, Zhiting; Zhang, Zhanbing; Zhang, Biyu; Zhu, Chenyu; Chen, Ke; Chuai, Guohui; Qu, Sheng; Xie, Lu; Gao, Yong; ...
  • Published: 31 Oct 2019
  • Publisher: figshare
Abstract
Abstract Background Cancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface in complex with major histocompatibility complex (MHC) class I proteins for recognition by cytotoxic T cells. Accurate and rapid identification of neoantigens play a pivotal role in cancer immunotherapy. Although several in silico tools for neoantigen prediction have been presented, limitations of these tools exist. Results We developed pTuneos, a computational pipeline for prioritizing tumor neoantigens from next-generation sequencing data. We tested the performance of pTuneos on the melanoma cancer vaccine cohort data and tumor-infiltrating lymphoc...
Subjects
free text keywords: 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified, Space Science, Genetics, Molecular Biology, Immunology, Cancer, FOS: Biological sciences, FOS: Clinical medicine, FOS: Computer and information sciences
Communities
Science and Innovation Policy Studies
Download fromView all 3 versions
figshare
Dataset . 2019
Provider: Datacite
figshare
Dataset . 2019
Provider: Datacite
Abstract
Abstract Background Cancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface in complex with major histocompatibility complex (MHC) class I proteins for recognition by cytotoxic T cells. Accurate and rapid identification of neoantigens play a pivotal role in cancer immunotherapy. Although several in silico tools for neoantigen prediction have been presented, limitations of these tools exist. Results We developed pTuneos, a computational pipeline for prioritizing tumor neoantigens from next-generation sequencing data. We tested the performance of pTuneos on the melanoma cancer vaccine cohort data and tumor-infiltrating lymphoc...
Subjects
free text keywords: 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified, Space Science, Genetics, Molecular Biology, Immunology, Cancer, FOS: Biological sciences, FOS: Clinical medicine, FOS: Computer and information sciences
Communities
Science and Innovation Policy Studies
Download fromView all 3 versions
figshare
Dataset . 2019
Provider: Datacite
figshare
Dataset . 2019
Provider: Datacite
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