OptiType

Precision HLA typing from next-generation sequencing data

Authors: András Szolek, Benjamin Schubert, Christopher Mohr, Jonas Scheid Version: 1.5.0 License: BSD-3-Clause

Introduction

OptiType is a novel HLA genotyping algorithm based on integer linear programming, capable of producing accurate 4-digit HLA genotyping predictions from NGS data by simultaneously selecting all major and minor HLA Class I alleles.

Installation

Via pip (Recommended)

pip install optitype

From source

git clone https://github.com/FRED-2/OptiType.git
cd OptiType
pip install -e .

External Dependencies

OptiType requires external tools that cannot be installed via pip:

1. RazerS3 - Read mapper

   # Via conda/bioconda
   conda install -c bioconda razers3
   
   # Or build from source: https://github.com/seqan/seqan

2. ILP Solver - At least one of:

   • GLPK (open source)

     apt install glpk-utils  # Debian/Ubuntu
     conda install -c conda-forge glpk  # Conda

   • CBC (open source)

     apt install coinor-cbc  # Debian/Ubuntu
     conda install -c conda-forge coincbc  # Conda

   • CPLEX (commercial, free for academia)

Verify Installation

optitype check-deps

Quick Start

Command Line

# DNA sequencing (paired-end)
optitype run -i reads_1.fastq -i reads_2.fastq --dna -o results/

# RNA sequencing (single-end)
optitype run -i sample.fastq --rna -o results/

# Re-analyze from BAM
optitype run -i mapped.bam --dna -o results/

Python API

from optitype import run_hla_typing, HLATypingConfig

result = run_hla_typing(
    fastq_files=["sample_1.fastq", "sample_2.fastq"],
    seq_type="dna",
    config=HLATypingConfig(solver="cbc", threads=4)
)

print(result.best_result)
# {'A1': 'A*02:01', 'A2': 'A*03:01', 'B1': 'B*07:02', ...}

Usage

optitype run --help

Usage: optitype run [OPTIONS]

  Run HLA typing analysis.

Options:
  -i, --input PATH       Input FASTQ or BAM files (use multiple times for paired-end)
  -r, --rna              Input data is RNA sequencing
  -d, --dna              Input data is DNA sequencing (default)
  -o, --outdir PATH      Output directory for results (required)
  -p, --prefix TEXT      Output filename prefix (default: timestamp)
  -b, --beta FLOAT       Homozygosity detection parameter (0.0-0.1)
  -e, --enumerate INT    Number of solutions to enumerate
  --solver [glpk|cbc|cplex]  ILP solver to use
  --razers3 PATH         Path to RazerS3 binary
  --threads INT          Number of threads for mapping
  -v, --verbose          Enable verbose output
  -c, --config PATH      Path to config.ini file
  --help                 Show this message and exit

Additional Commands

# Check dependencies
optitype check-deps

# Generate config file
optitype init-config

# Show installation info
optitype info

Configuration

Generate a config file with:

optitype init-config -o config.ini

Key settings:

[mapping]
threads=4           # Threads for read mapping

[ilp]
solver=glpk        # ILP solver: glpk, cbc, or cplex
threads=1          # Threads for ILP solver

[behavior]
deletebam=true     # Delete intermediate BAM files
unpaired_weight=0  # Weight for unpaired reads (0-1)

Docker

docker pull fred2/optitype
docker run -v /path/to/data:/data -t fred2/optitype \
    -i /data/reads_1.fastq -i /data/reads_2.fastq --dna -o /data/results/

Test Examples

# DNA (paired-end)
optitype run \
    -i ./test/exome/NA11995_SRR766010_1_fished.fastq \
    -i ./test/exome/NA11995_SRR766010_2_fished.fastq \
    --dna -v -o ./test/exome/

# RNA (paired-end)
optitype run \
    -i ./test/rna/CRC_81_N_1_fished.fastq \
    -i ./test/rna/CRC_81_N_2_fished.fastq \
    --rna -v -o ./test/rna/

Output

OptiType produces:

• *_result.tsv - HLA typing results
• *_coverage_plot.pdf - Coverage visualization

Example output:

	A1	A2	B1	B2	C1	C2	Reads	Objective
0	A*02:01	A*03:01	B*07:02	B*44:02	C*07:02	C*05:01	1234	1156.5

Migration from v1.x

Version 1.5 introduces a modernized CLI. Main changes:

• Install with pip install optitype
• Use optitype run instead of python OptiTypePipeline.py
• Multiple input files: use -i file1 -i file2 instead of -i file1 file2
• Data bundled with package (no need to set paths)

The core algorithm and output format remain unchanged.

Requirements

• Python 3.10+
• External: RazerS3, ILP solver (GLPK/CBC/CPLEX)

Reference

Szolek, A, Schubert, B, Mohr, C, Sturm, M, Feldhahn, M, and Kohlbacher, O (2014). OptiType: precision HLA typing from next-generation sequencing data Bioinformatics, 30(23):3310-6. doi:10.1093/bioinformatics/btu548

Contact

András Szolek szolek@informatik.uni-tuebingen.de University of Tübingen, Applied Bioinformatics