neoepiscopeimproves neoepitope prediction with multi-variant phasing

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 developedneoepiscopechiefly 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.neoepiscopeis performant, flexible, and supports several major histocompatibility complex binding affinity prediction tools. We have releasedneoepiscopeas open-source software (MIT license,https://github.com/pdxgx/neoepiscope) for broad use.KEY POINTSGermline context and somatic variant phasing are important for neoepitope predictionMany popular neoepitope prediction tools have issues of performance and reproducibilityWe describe and provide performant software for accurate neoepitope prediction from DNA-seq data