Pepitope facilitates TCR-neoantigen screen analysis in the R language

Area of Science:

• Immunology
• Bioinformatics
• Computational Biology

Background:

• T cell receptor (TCR)-neoantigen screening is crucial for personalized immunotherapy and mechanistic studies.
• Existing computational tools lack integrated modules for experimental screening support.
• There is a need for a comprehensive software package to bridge the gap between computational analysis and experimental screening.

Purpose of the Study:

• To present pepitope, an R package designed to facilitate the analysis of TCR-neoantigen co-culture screens.
• To integrate minigene library generation, sequencing-based quality control, and differential abundance analysis into a single workflow.
• To lower the barrier for biologists to perform end-to-end co-culture screen analyses.

Main Methods:

• The pepitope package utilizes Bioconductor annotation resources for peptide extraction from tumor variants.
• It includes modules for demultiplexing and barcode counting for construct quality control.
• Differential abundance testing is performed using a negative-binomial model based on DESeq2 for identifying immunogenic epitopes.

Main Results:

• pepitope successfully integrates multiple steps of co-culture screen analysis within the R/Bioconductor ecosystem.
• The package provides robust quality control and differential testing capabilities for identifying immunogenic neoantigens.
• It enables researchers to perform comprehensive analyses without requiring extensive computational expertise.

Conclusions:

• pepitope offers a unified and accessible solution for analyzing TCR-neoantigen co-culture screens.
• The package empowers laboratory-based biologists to conduct sophisticated analyses, advancing personalized immunotherapy research.
• By integrating diverse analytical modules, pepitope streamlines the workflow from library generation to identifying immunogenic epitopes.