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• W2890824233 abstract "ABSTRACT The vast majority of tools for neoepitope prediction from DNA sequencing of complementary tumor and normal patient samples do not consider germline context or the potential for co-occurrence of two or more somatic variants on the same mRNA transcript. Without consideration of these phenomena, existing approaches are likely to produce both false positive and false negative results, resulting in an inaccurate and incomplete picture of the cancer neoepitope landscape. We developed neoepiscope chiefly to address this issue for single nucleotide variants (SNVs) and insertions/deletions (indels), and herein illustrate how germline and somatic variant phasing affects neoepitope prediction across multiple datasets. We estimate that up to ∼5% of neoepitopes arising from SNVs and indels may require variant phasing for their accurate assessment. neoepiscope is performant, flexible, and supports several major histocompatibility complex binding affinity prediction tools. We have released neoepiscope as open-source software (MIT license, https://github.com/pdxgx/neoepiscope ) for broad use. KEY POINTS Germline context and somatic variant phasing are important for neoepitope prediction Many popular neoepitope prediction tools have issues of performance and reproducibility We describe and provide performant software for accurate neoepitope prediction from DNA-seq data" @default.
• W2890824233 created "2018-09-27" @default.
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• W2890824233 date "2018-09-14" @default.
• W2890824233 modified "2023-09-27" @default.
• W2890824233 title "neoepiscopeimproves neoepitope prediction with multi-variant phasing" @default.
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• W2890824233 doi "https://doi.org/10.1101/418129" @default.
• W2890824233 hasPublicationYear "2018" @default.
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