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RabadanLab / arcasHLA

Fast and accurate in silico inference of HLA genotypes from RNA-seq
GNU General Public License v3.0
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Dependencies

Install arcasHLA through bioconda with:

conda install arcas-hla -c bioconda -c conda-forge

Important: Please include channels bioconda and conda-forge as above.

arcasHLA can also be installed through the environment.yml file in this repo:

conda env create -f environment.yml
conda activate arcas-hla

Test

(Update 2023-09-29): The below tests are now implemented as a pytest suite. You can run this locally by building the docker environment and running pytest. From the current directory:

docker build -t <image-name> -f Docker/Dockerfile .
docker run --rm -v /path/to/repo:/app <image-name> pytest

In order to test arcasHLA partial typing, we need to roll back the reference to an earlier version. First, fetch IMGT/HLA database version 3.24.0:

./arcasHLA reference --version 3.24.0

Extract reads:

./arcasHLA extract test/test.bam -o test/output -t 8 -v

Genotyping (no partial alleles):

./arcasHLA genotype test/output/test.extracted.1.fq.gz test/output/test.extracted.2.fq.gz -g A,B,C,DPB1,DQB1,DQA1,DRB1 -o test/output -t 8 -v

Expected output in test/output/test.genotype.json:

{"A": ["A*01:01:01", "A*03:01:01"], 
 "B": ["B*39:01:01", "B*07:02:01"], 
 "C": ["C*08:01:01", "C*01:02:01"], 
 "DPB1": ["DPB1*14:01:01", "DPB1*02:01:02"], 
 "DQA1": ["DQA1*02:01:01", "DQA1*05:03"], 
 "DQB1": ["DQB1*02:02:01", "DQB1*06:09:01"], 
 "DRB1": ["DRB1*10:01:01", "DRB1*14:02:01"]}

Partial typing:

./arcasHLA partial test/output/test.extracted.1.fq.gz test/output/test.extracted.2.fq.gz -g A,B,C,DPB1,DQB1,DQA1,DRB1 -G test/output/test.genotype.json -o test/output -t 8 -v

Expected output in test/output/test.partial_genotype.json:

{"A": ["A*01:01:01", "A*03:01:01"], 
 "B": ["B*07:02:01", "B*39:39:01"],
 "C": ["C*08:01:01", "C*01:02:01"], 
 "DPB1": ["DPB1*14:01:01", "DPB1*02:01:02"], 
 "DQA1": ["DQA1*02:01:01", "DQA1*05:03"],
 "DQB1": ["DQB1*06:04:01", "DQB1*02:02:01"],
 "DRB1": ["DRB1*03:02:01", "DRB1*14:02:01"]}

Remember to update the HLA reference using the following command.

./arcasHLA reference --update

Usage

To see the list of available tools, simply enter arcasHLA. To view the required and optional arguments for any of the tools enter arcasHLA [command] -h.

Extract reads

arcasHLA takes sorted BAM files and extracts chromosome 6 reads and related HLA sequences. If the BAM file is not indexed, this tool will run samtools index before extracting reads. By default, extract outputs paired FASTQ files; use the --single flag for single-end samples.

arcasHLA extract [options] /path/to/sample.bam

Output: sample.extracted.1.fq.gz, sample.extracted.2.fq.gz

Options:

Genotype

From FASTQs

To predict the most likely genotype (no partial alleles), input the FASTQs produced by extract or the original FASTQs with all reads (experimental - use with caution).

arcasHLA genotype [options] /path/to/sample.1.fq.gz /path/to/sample.2.fq.gz

Output: sample.alignment.p, sample.em.json, sample.genotype.json

From intermediate alignment file

If you have previously run genotype on a sample, you can run genotype again directly from sample.alignment.p to retype without aligning with Kallisto again. This is useful if you want to try different populations, genes and other parameters.

arcasHLA genotype [options] /path/to/sample.alignment.p

Example .genotype.json

{'A': ['A*01:01:01', 'A*29:02:01'],
 'B': ['B*08:01:01', 'B*44:03:01'],
 'C': ['C*07:01:01', 'C*16:01:01'],
 'DQA1': ['DQA1*02:01:01', 'DQA1*05:01:01'],
 'DQB1': ['DQB1*02:01:01', 'DQB1*02:02:01'],
 'DRB1': ['DRB1*03:01:01', 'DRB1*07:01:01']}

Options

Genotype - partial (optional)

Following genotyping, partial alleles can be predicted. This requires aligning the reads to an alternate, partial allele reference. The sample.genotype.json file from the previous step is required.

arcasHLA partial [options] -G /path/to/sample.genotype.json /path/to/sample.1.fq.gz /path/to/sample.2.fq.gz

Output: sample.partial_alignment.p, sample.partial_genotype.json

The options for partial typing are the same as genotype. Partial typing can be run from the intermediate alignment file.

Merge jsons

To make analysis easier, this command will merge all jsons produced by genotyping into a single table. All .genotype.json files will be merged into a single run.genotypes.tsv file and all .partial_genotype.json files will be merged into run.partial_genotypes.tsv. In addition, HLA locus read counts and relative abundance produced by alignment will be merged into a single tsv file.

arcasHLA merge [options]

Options

Convert HLA nomenclature

arcasHLA convert changes alleles in a tsv file from its input form to a specified grouped nomenclature (P-group or G-group) or a specified number of fields (i.e. 1, 2 or 3 fields in resolution). This file can be produced by arcasHLA merge or any tsv following the same structure:

subject A1 A2 B1 B2 C1 C2
subject_name A*01:01:01 A*01:01:01 B*07:02:01 B*07:02:01 C*04:01:01 C*04:01:01

P-group (alleles sharing the same amino acid sequence in the antigen-binding region) and G-group (alleles sharing the same base sequence in the antigen-binding region) can only be reduced to 1-field resolution as alleles with differing 2nd fields can be in the same group. By the same reasoning, P-group cannot be converted into G-group.

arcasHLA convert --resolution [resolution] genotypes.tsv

Options

Change reference

To update the reference to the latest IMGT/HLA version, run

arcasHLA reference --update

If you are running multiple tools to type HLAs, it can be helpful to use the same version of IMGT/HLA. You can select the version you like using the commithash from the IMGT/HLA Github.

arcasHLA reference --version [commithash]

If you suspect there is an issue with the reference files, rebuild the reference with the following command

arcasHLA reference --rebuild

Note: if your reference was built with arcasHLA version <= 0.1.1 and you wish to change your reference to versions >= 3.35.0, it may be necessary to remove the IMGTHLA folder due to the need for Git Large File Storage to properly download hla.dat.

rm -rf dat/IMGTHLA
arcasHLA reference --update

Options

Build Customized References

Input: arcasHLA genotypes.json

Customized references can be built from arcasHLA genotype outputs.

./arcasHLA customize genotypes.json -o ~/ref

Input: HLA tsv

Customized references can be built from a tab-separated file with the following structure:

subject A1 A2 B1 B2 C1 C2
Example A*01:01 A*02:01 B*07:01 B*52:01 C*04:01 C*18:01 
./arcasHLA customize hla.tsv -o ~/ref

Options:

usage: arcasHLA customize [options]

optional arguments:
  -h, --help            show this help message and exit

  -G , --genotype       comma-separated list of HLA alleles (e.g. A*01:01,A*11:01,...)
                        arcasHLA output genotype.json or genotypes.json
                        or tsv with format specified in README.md
  -s , --subject        subject name, only required for list of alleles
  -g , --genes          comma separated list of HLA genes
                        default: all
                        options: A, B, C, DMA, DMB, DOA, DOB, DPA1, DPB1, DQA1,
                        DQB1, DRA, DRB1, DRB3, DRB5, E, F, G, H, J, K, L

  --transcriptome TRANSCRIPTOME
                        transcripts to include besides input HLAs
                         options: full, chr6, none
                          default: full

  --resolution RESOLUTION
                        genotype resolution, only use >2 when typing performed with assay or Sanger sequencing
                          default: 2

  --grouping GROUPING   type/number of transcripts to include per allele
                         single - one 3-field resolution transcript per allele (e.g. A*01:01:01)
                        g-group - all transcripts with identical binding regions
                          default: protein group - all transcripts with identical protein types (2 fields the same)

  -o , --outdir         out directory

  --temp                temp directory

  --keep_files          keep intermediate files

  -t , --threads
  -v, --verbose

Quantification

Note: if the reference was built with the --chr6 flag, you should run quant with extracted chromosome 6 FASTQs (see extract).

./arcasHLA quant --ref /path/to/ref/sample FASTQ

Example:

./arcasHLA quant --ref ~/ref/Pt23 -t 8 -o /Volumes/quant/ /Volumes/fastq/Pt23_pre.1.fq.gz /Volumes/fastq/Pt23_pre.2.fq.gz

Options:

usage: arcasHLA quant [options] FASTQs

positional arguments:
  file               list of fastq files

optional arguments:
  -h, --help         show this help message and exit

  --sample SAMPLE    sample name
  --ref              arcasHLA quant_ref path (e.g. "/path/to/ref/sample")

  -o , --outdir      out directory

  --temp             temp directory

  --keep_files       keep intermediate files

  -l AVG, --avg AVG  Estimated average fragment length for single-end reads
                       default: 200

  -s STD, --std STD  Estimated standard deviation of fragment length for single-end reads
                       default: 20

  --single           Include flag if single-end reads. Default is paired-end.

  -t , --threads
  -v, --verbose

Citations