NeoPrioProject

Overview

NeoPrioProject is a Python-based project designed to prioritize neoepitopes using a rank sum algorithm based on neofox features.

Features

• Identifies neoepitope candidates based on binding affinity utilizing pVACseq
• Prioritizes neoepitopes based on various neofox features
• Extracts feature importance based on machine learning classifier
• Utilizes rank sum algorithm and relative quantile-based quality score for scoring
• Analyzes features as well as identification and prioritization outputs

Installation

To install the necessary dependencies, run:

pip install -r requirements.txt

Usage

To identify neoepitope candidates for a patient with pVACseq, run the following command:

python identification/run_pvacseq.py -i <path_to_vcf_file> --strelka --data_dir <path_to_directory_containing_all_sequencing_data>

To annotate neoepitope candidates with neofox, run:

python prioritization/run_neofox.py -s <sample-name> -n <normal_name> --strelka --data_dir <path_to_directory_containing_all_sequencing_data>

To prioritize neoepitopes within a patient using immunogenicity score, run the following command:

python prioritization/neoantigen_prioritization_rank_sum.py --pvacseq-filtered-output <path_to_pvacseq_filtered_output> --neofox-output <path_to_neofox_output>

For machine learning model implementation, evaluation and feature importance analysis, see XGBoost Classifier Model

Prerequisites

• Ensure that VcfFilter is in your system's PATH