weizhiting / itunes

iTunes: identification of personalized Tumor neoantigens from next-generation sequencing data

iTunes: identification of personalized Tumor neoantigens from next-generation sequencing data

iTunes is the state-of-the-art computational pipeline for identifying personalized tumor neoantigens from next-generation sequencing data. With raw whole-exome sequencing data and/or RNA-seq data, iTunes calculates five important immunogenicity features to construct a machine learning-based classifier (vitroneo) to predict and prioritize neoantigens with strong in vitro immunologic effects, followed by an efficient score scheme (vivoneo) to identify neoantigens with in vivo immunologic effects.

Authors:

Chi Zhou and Qi Liu

Citation:

iTunes: identification of personalized Tumor neoantigens from next-generation sequencing data, Submitted, 2018.

Web sever:

TBD

Dependencies

Hardware:

iTunes currently test on x86_64 on ubuntu 16.04.

Required software:

• Python 2.7
• R 3.2.3
• NetMHCpan 4.0
• Variant Effect Predictor (VEP)
• BWA
• samtools
• strelka
• Optitype
• Pyclone
• GATK 3.8
• Picard tools
• Java 8
• Varscan2
• kallisto
• trimmomatic
• vcftools
• blast
• tabix
• gawk

Required Python package:

• yaml
• XGboost
• biopython
• scikit-learn==0.19.1
• pandas
• numpy
• imblearn
• Pyomo
• tables
• pysam
• PypeR
• multiprocessing
• subprocess
• math
• matplotlib
• collections

Required R package:

• cpynumber
• sequenza
• squash

Installation

Install via Docker

Docker image of iTunes is at https://hub.docker.com/r/bm2lab/itunes/. See the user manual for a detailed description usage.

Install from source

1. Install all software listed above.

2. Download or clone the iTunes repository to your local system:

    git clone https://github.com/bm2-lab/iTunes.git
   

3. Obtain the reference files from GRCh38. These include cDNA, peptide; please refer to user manual for a detailed description.

Usage

iTunes has two modes, WES mode and VCF mode.

PairMatchDna mode accepts WES and RNA-seq sequencing data as input, it conduct sequencing quality control, mutation calling, hla typing, expression profiling and neoantigen prediction, filtering, annotation.

VCF mode accepts mutation VCF file, expression profile, copy number profile and tumor cellularity as input, it performs neoantigen prediction, filtering, annotation directly on input file.

You can use these two mode by:

    python iTunes.py WES -i config_WES.yaml

or

    python iTunes.py VCF -i config_VCF.yaml

User Manual

For detailed information about usage, input and output files, test examples and data preparation please refer to the iTunes User Manual

Contact

[email protected] or [email protected] Tongji University, Shanghai, China