nf-core/hlatyping

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Introduction

nf-core/hlatyping is a bioinformatics pipeline that can be used to perform HLA typing from next-generation sequencing data. The pipeline does next-generation sequencing-based Human Leukozyte Antigen (HLA) typing using OptiType. OptiType is a HLA genotyping algorithm based on integer linear programming. Reads of whole exome/genome/transcriptome sequencing data are mapped against a reference of known MHC class I alleles. To produce accurate 4-digit HLA genotyping predictions, all major and minor HLA-I loci are considered simultaneously to find an allele combination that maximizes the number of explained reads.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!

On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the nf-core website.

Pipeline summary

1. Read QC (FastQC)
2. Generate reference indices (yara)
3. Map reads to reference (yara)
4. Run HLA typing (OptiType)
5. Present QC for raw reads (MultiQC)

Usage

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

sample,fastq_1,fastq_2,seq_type
CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz,dna

Each row represents a sample and its fastq file (single-end) or a pair of fastq files (paired end) and the sequencing type. The sample identifiers have to be specified with the fastq files and the sequencing type, i.e. dna or rna. It is also possible to provide reads as bam file by adding a column bam in which the file path will be specified. The fastq columns have to be kept.

The pipeline will auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet.

Now, you can run the pipeline using:

nextflow run nf-core/hlatyping \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --outdir <OUTDIR>

see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/hlatyping was originally written by Christopher Mohr from Medical Data Integration Center and Quantitative Biology Center, Alexander Peltzer from Boehringer Ingelheim, and Sven Fillinger from Quantitative Biology Center.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don’t hesitate to get in touch on the Slack #hlatyping channel (you can join with this invite).

Citations

If you use nf-core/hlatyping for your analysis, please cite it using the following doi: 10.5281/zenodo.1401039

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.