Evidence map›Paper›PMID 42482167›Full record

ArticleBioinformatics (Oxford, England)2026

Pepitope facilitates TCR-neoantigen screen analysis in the R language.

Moritz Broft, Wouter Scheper, Michael Schubert

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Moritz BroftInstitute of Bioinformatics, Medical University of Innsbruck, Innrain 80, 6020 Innsbruck, Austria.
Wouter ScheperDivision of Molecular Oncology and Immunology, Oncode Institute, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX, the Netherlands.ORCID 0000-0003-1555-587X
Michael SchubertInstitute of Bioinformatics, Medical University of Innsbruck, Innrain 80, 6020 Innsbruck, Austria.ORCID 0000-0002-6862-5221

Funding

the Dutch Cancer Society (KWF Kankerbestrijding) 11877the Dutch Cancer Society (KWF Kankerbestrijding) 2020-1/12977
6 · The paper itself

Abstract

motivationFunctional screening of patient-derived T cell receptor (TCR)-neoantigen pairs via co-culture experiments is a way to design personalised immunotherapy or to investigate its mechanism of action. Current computational toolkits can either generate and prioritise candidate epitopes from tumour variants or count barcodes in sequencing data. However, they lack modules to support experimental screening, such as sample demultiplexing, construct quality control, and downstream analysis. To bridge these gaps, we present pepitope, an R package that integrates minigene library generation, sequencing-based quality control (QC), and differential abundance analysis of co-culture screens into a single software package within the accessible R/Bioconductor ecosystem.

resultspepitope workflows include the extraction of mutant and reference peptides with customisable flanking regions from tumour variant calls using Bioconductor annotation resources; demultiplexing and barcode counting for construct QC; and negative-binomial-based differential testing built on DESeq2 to identify immunogenic epitopes in TCR co-culture assays. By remaining within R, pepitope lowers the barrier for lab-based biologists familiar with R and Bioconductor to perform end-to-end co-culture screen analyses without needing dedicated computational support. AVAILABILITY: pepitope (R ≥ 4.5.0) is freely available on GitHub under the GPL-3.0 license, with detailed vignettes hosted at https://mschubert.github.io/pepitope/. Installation is facilitated via the remotes package in R.

Indexed as

Antigens, NeoplasmComputational BiologyReceptors, Antigen, T-CellSoftwareCoculture TechniquesHumansAntigens, NeoplasmReceptors, Antigen, T-Cell

Identifiers

PMID42482167
PMCPMC13452055

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.