Disruption of the class I human leukocyte antigen (HLA) molecules has important implications for immune evasion and tumor evolution. To evaluate the extent of genomic and transcriptomic HLA disruption, we developed MHC Hammer, which has the following four major components: (1) identifying allele-specific HLA somatic mutations, (2) calculating HLA LOH, (3) evaluating HLA allele-specific repression and (4) identifying allele-specific HLA alternative splicing.
You can find our MHC Hammer publication here: https://www.nature.com/articles/s41588-024-01883-8
MHC Hammer requires every patient to have a whole exome sequencing (WES) germline blood sample. In addition, MHC Hammer requires the following inputs:
To estimate DNA HLA allelic imbalance and somatic mutations:
Install Nextflow
(>=21.10.3
)
Install Singularity
You need to create a inventory file with the following columns:
tumour
or normal
. Required.wxs
or rnaseq
. Required.wxs
this is the matched germline WXS. When sequencing_type is rnaseq
this is the matched RNAseq normal name. Can be left empty.The inventory should be a csv file and is input to the pipeline with the --input
parameter.
The following is an example inventory for a single patient with:
patient | sample_name | sample_type | bam_path | sequencing_type | purity | ploidy | normal_sample_name |
---|---|---|---|---|---|---|---|
patient1 | sample_name1 | tumour | path/to/sample_name1.bam | wxs | 0.5 | 3 | sample_name3 |
patient1 | sample_name2 | tumour | path/to/sample_name2.bam | wxs | 0.3 | 2.5 | sample_name3 |
patient1 | sample_name3 | normal | path/to/sample_name3.bam | wxs | |||
patient1 | sample_name1 | tumour | path/to/sample_name4.bam | rnaseq | sample_name4 | ||
patient1 | sample_name4 | normal | path/to/sample_name5.bam | rnaseq |
git clone git@github.com:McGranahanLab/mhc-hammer.git
mkdir mhc-hammer/singularity_images
cd mhc-hammer
project_dir=${PWD}
The MHC Hammer refernece files are created from sequences stored in the IMGT database. We have created MHC Hammer references from two IMGT versions:
This should download two folders, kmer_files
and mhc_references
. Save these folders in the assets folder:
assets/kmer_files/imgt_30mers.fa
- This file contains all 30mers created from the sequences in the IMGT database. For an overview of how this file was created see docs/mhc_reference_files.md
assets/mhc_references
- this folder contains the MHC reference files used in the MHC Hammer pipeline. For an overview of how these file were created see docs/mhc_reference_files.md
Every sample run through MHC Hammer requires HLA allele types. MHC Hammer provides three options for typing HLA alleles:
The HLA allele types predicted by HLA-HD (option 1 or 2) or input to MHC Hammer (option 3) must match the alleles in the MHC Hammer reference files
This means that if using HLA-HD within MHC Hammer (option 1 or 2) the reference version used by HLA-HD must be the same as the IMGT reference version used to create the MHC Hammer reference files. If HLA allele types are input to MHC Hammer, these allele types must be present in the MHC Hammer reference files. More information on this is prodived below.
The steps are as follows:
On the HLA-HD website fill in the download request form to get a download link for HLA-HD
Move the downloaded hlahd.version.tar.gz file into the project bin directory.
mv /path/to/hlahd_download.tar.gz ${project_dir}/bin/
Run the install_hlahd.sh script. This script will:
${project_dir}/bin/
directory. This install_hlahd.sh
script requires:
$project_dir/singularity_images/
folder (see below)hlahd_download
variable to be set as the path to /path/to/hlahd_download.tar.gz.To download the mhc_hammer_preprocessing_latest.sif container:
cd ${project_dir}/singularity_images
singularity pull --arch amd64 library://tpjones15/default/mhc_hammer_preprocessing:latest
mhc_hammer_preprocessing_sif="${project_dir}/singularity_images/mhc_hammer_preprocessing_latest.sif"
Then, run install_hlahd.sh
:
bash ${project_dir}/scripts/install_hlahd.sh -p ${project_dir} -h ${hlahd_download}
If you want to use a different version of the IMGT database with HLA-HD you can change line 14 in bin/update.dictionary.alt.sh
to your choosen version of the IMGT database:
wget https://github.com/ANHIG/IMGTHLA/raw/3550/hla.dat.zip ## this downloads version 3.55
## For example, for version 3.38, replace line above with:
wget https://github.com/ANHIG/IMGTHLA/raw/3380/hla.dat.zip
## Or, for the latest version:
wget https://github.com/ANHIG/IMGTHLA/raw/Latest/hla.dat.zip
Remember that the HLA-HD database version should match the version used to create the files in the assets/mhc_references
folder.
When running the pipeline ensure you run with --hlahd_local_install true (default)
We are unable to provide a singularity container for HLA-HD tool. Instead, we have provided steps to create your own container:
assets/hlahd_container.def
file:
/path/to/downloaded/hlahd.version.tar.gz
in the %files
section /path/to/project_dir/bin/update.dictionary.alt.sh
in the %files
section HLAHD_VERSION
variable in the %post
section singularity build hlahd.sif assets/hlahd_container_template.def
mv hlahd.sif singularity_images
When running the MHC Hammer pipeline ensure you run with --hlahd_local_install false
.
If you want to use a different version of the IMGT database with HLA-HD you can change line 14 in bin/update.dictionary.alt.sh
to your choosen version of the IMGT database before building the image:
wget https://github.com/ANHIG/IMGTHLA/raw/3550/hla.dat.zip ## this downloads version 3.55
## For example, for version 3.38, replace line above with:
wget https://github.com/ANHIG/IMGTHLA/raw/3380/hla.dat.zip
## Or, for the latest version:
wget https://github.com/ANHIG/IMGTHLA/raw/Latest/hla.dat.zip
Remember that the HLA-HD database version should match the version used to create the files in the assets/mhc_references
folder.
If you already have HLA allele types for your samples you can skip the HLA-HD step in the pipeline. To do this:
hla_alleles_path
that contains the path to a csv file listing the HLA alleles. This table should have three columns with no column names. The columns are:
An example of the file format can be found here: https://github.com/McGranahanLab/mhc-hammer/blob/main/test/data/SIM001_hla_alleles.csv
--run_hlahd false
flag.Remember that the alleles input to MHC Hammer must be present in the MHC Hammer reference files in the assets/mhc_references
folder. You can get a list of alleles from the fasta file, e.g. grep '^>' assets/mhc_references/mhc_genome.fasta
The conf/hpc.config
file controls how the pipeline is run on your HPC system. Before running the pipeline you may want to update the variables in conf/hpc.config
to suit your HPC system. In particular, it might be useful to specify the singularity bind directory by adding
singularity {
runOptions = "-B /bind_directory"
}
to conf/hpc.config
, and changing bind_directory
to your choosen path. You may also need to add the name of your HPC queue by adding
process {
queue = 'cpu'
}
to conf/hpc.config
, and changing cpu
to the name of the HPC queue that you are using.
Alternatively, if it exists, you can use a config file specific for your institute. See this page for more information on nextflow config files.
You can change the MHC Hammer pipeline parameters from the default in the nextflow.conf
file. Alternatively, you can change the parameters by inputting them directly when you run the pipeline. For a full overview of the pipeline parameters run:
nextflow run main.nf --help --show_hidden_params
To run the MHC Hammer pipeline:
nextflow run main.nf \
--input /path/to/inventory \
-c conf/hpc.config -resume
This command needs to be run from the project directory.
The -resume
flag tells the pipeline to not rerun tasks that have sucessfully completed. See this page for more information on Nextflow caching.
To change a pipeline parameter, either change the parameter in the nextflow.conf
file, or directly as an input to the pipeline. Parameters input to the pipeline take precedence over parameters in the nextflow.conf
file. For example, to change the min_depth
parameter:
nextflow run main.nf \
--input /path/to/inventory \
-c conf/hpc.config \
--min_depth 5 -resume
If you already have subsetted BAM files and flagstat output, you can input these to the MHC Hammer pipeline instead of rerunning these steps. To do this:
bam_path
column in the inventory file should contain the path to the subsetted BAM fileslibrary_size_path
that contains the path to a text file with the library size for the sample. This can be calculated from the flagstat output. --run_bam_subsetting false
flag.By defult, the output is saved in the working directory in a folder called mhc_hammer_results
. See docs/mhc_hammer_outputs.md
for an overview of all outputs from MHC Hammer.
A test dataset is provided. The input BAMs and inventory are in the test/data
folder. Note that you will need to update the inventory columns bam_path
and hla_alleles_path
so that they contain the full paths to the files.
To run the pipeline with the test dataset, including the HLA-HD step:
nextflow run main.nf -profile test,singularity --input test/data/mhc_hammer_test_inventory.csv
To run the pipeline with the test dataset, without the HLA-HD step:
nextflow run main.nf -profile test,singularity --input test/data/mhc_hammer_test_inventory.csv --run_hlahd false
The output will be saved in the test/results
folder.
Files downloaded with the git repository
codon_table.csv
- contains a mapping between codons and amino acids, this is used to determine the consequence of alternate splicing events in the HLA alleles.contigs_placeholder.txt
- This is a placeholder for the subset BAM module. It will be ignored if user inputs a new path to a contigs file.hlahd_container_template.def
- A template for making a HLA-HD singularity filemhc_coords_chr6.txt
- these genomic coordinates can be used when subsetting the bams. Any reads falling within these coordinates are included in the subsetted bams. strand_info.txt
- contains a mapping between the HLA gene and the strand (forward="+" or reverse="-")transcriptome_placeholder.txt
- A placeholder so the pipeline will run with only WXS data.This pipeline uses code and infrastructure developed and maintained by the nf-core initative, and reused here under the MIT license.
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.
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.