HLA Annotation (HLAnn) Python package for annotating HLA
Project description
HLA Annotation Pipeline
Table of Contents
Background ⤴
In many cases, modern HLA nomenclature cannot fully describe the various genetic polymorphisms between both primary and reference data, as well as between recipients and stem cell sources. This tool addresses this issue by integrating sequence data with HLA nomenclature to facilitate research into some of these less-accessible genetic polymorphisms. Additionally, various mismatching models (HLA-B leader and HLA-DPB1 expression/TCE, for instance) have been built-in to provide an aggregating hub for aiding in clinical decision-making. This operating procedure details the usage and deployment of this tool.
Tools ⤴
Python Package ⤴
Installation
pip install .
Setup
from hlann.hlann import HLAnn
hlann = HLAnn(db_version='3470', verbose=True)
Usage
Allotype
Command
hlann.annotate_allotype('DPB1*01:AETTG')
Result
{'name': 'DPB1*01:AETTG',
'tce': '3',
'resolution': 'intermediate',
'matched': False,
'expr_level': '~high',
'expr_annot_type': '~experimental',
'alleles': [{'allele_expr': 'DPB1*01:01',
'CIWD_TOTAL': 'C',
'exon3_motif_ref': 'ACCACTC',
'utr3_motif_ref': 'G',
'tce': '3',
'resolution': 'high',
'expr_level': 'high',
'experimental': True},
{'allele_expr': 'DPB1*162:01',
'CIWD_TOTAL': 'WD',
'exon3_motif_ref': 'GTTGTCT',
'utr3_motif_ref': 'A',
'tce': '3',
'resolution': 'high',
'expr_level': 'low',
'experimental': False},
{'allele_expr': 'DPB1*417:01',
'CIWD_TOTAL': 'WD',
'exon3_motif_ref': 'ACCACTC',
'utr3_motif_ref': 'unknown',
'tce': '3',
'resolution': 'high',
'expr_level': 'high',
'experimental': False}]}
Genotype
Command
hlann.annotate_genotype('DPB1*01:AETTA+DPB1*04:AETTB')
Result
{
"allele_one": {
"alleles": [
{
"CIWD": "C",
"allele_expr": "DPB1*01:01",
"exon3_motif_ref": "ACCACTC",
"experimental": true,
"expr_level": "high",
"resolution": "high",
"tce": "3",
"utr3_motif_ref": "G"
},
{
"CIWD": "WD",
"allele_expr": "DPB1*417:01",
"exon3_motif_ref": "ACCACTC",
"experimental": false,
"expr_level": "high",
"resolution": "high",
"tce": "3",
"utr3_motif_ref": "unknown"
}
],
"expr_annot_type": "experimental",
"expr_level": "high",
"matched": false,
"name": "DPB1*01:AETTA",
"resolution": "intermediate",
"tce": "3"
},
"allele_two": {
"alleles": [
{
"CIWD": "C",
"allele_expr": "DPB1*04:01",
"exon3_motif_ref": "GTTGTCT/GTTGCCT/GTTATCT",
"experimental": true,
"expr_level": "low",
"resolution": "high",
"tce": "3/0",
"utr3_motif_ref": "A"
},
{
"CIWD": "C",
"allele_expr": "DPB1*126:01",
"exon3_motif_ref": "GTTGTCT",
"experimental": false,
"expr_level": "low",
"resolution": "high",
"tce": "3",
"utr3_motif_ref": "A"
},
{
"CIWD": "I",
"allele_expr": "DPB1*350:01",
"exon3_motif_ref": "ACCACTC",
"experimental": false,
"expr_level": "high",
"resolution": "allelic",
"tce": "3",
"utr3_motif_ref": "unknown"
},
{
"CIWD": "WD",
"allele_expr": "DPB1*415:01",
"exon3_motif_ref": "GTTGTCT",
"experimental": false,
"expr_level": "low",
"resolution": "allelic",
"tce": "3",
"utr3_motif_ref": "A"
}
],
"expr_annot_type": "~experimental",
"expr_level": "~low",
"matched": false,
"name": "DPB1*04:AETTB",
"resolution": "intermediate",
"tce": "3"
},
"genotype": "DPB1*01:AETTA+DPB1*04:AETTB"
}
Matches
Command
hlann.annotate_match('DPB1*04:01+DPB1*40:01', 'DPB1*40:01+DPB1*40:01')
Result
{
"directionality": "GvH",
"genotype_donor": {
"allele_one": {
"alleles": null,
"expr_annot_type": "experimental",
"expr_level": "low",
"matched": true,
"name": "DPB1*40:01",
"resolution": "high",
"tce": "3"
},
"allele_two": {
"alleles": null,
"expr_annot_type": "experimental",
"expr_level": "low",
"matched": true,
"name": "DPB1*40:01",
"resolution": "high",
"tce": "3"
},
"genotype": "DPB1*40:01+DPB1*40:01"
},
"genotype_recipient": {
"allele_one": {
"alleles": null,
"expr_annot_type": "experimental",
"expr_level": "low",
"matched": false,
"name": "DPB1*04:01",
"resolution": "high",
"tce": "3"
},
"allele_two": {
"alleles": null,
"expr_annot_type": "experimental",
"expr_level": "low",
"matched": true,
"name": "DPB1*40:01",
"resolution": "high",
"tce": "3"
},
"genotype": "DPB1*04:01+DPB1*40:01"
},
"grade": "MA",
"matched_alleles_don": [
"DPB1*40:01",
"DPB1*40:01"
],
"matched_alleles_pat": [
"DPB1*40:01"
],
"mismatched_allele_pat_expr_level": "low",
"mismatched_alleles_don": [],
"mismatched_alleles_pat": [
"DPB1*04:01"
],
"tce_match": "Permissive"
}
HLA Annotation Pipeline ⤴
Bootstrapping
To begin, ensure that you have Python3 (3.9 was used for this project) installed. To check, issue this command to verify your python version:
python --version
If Python3 is not installed, please download it from here.
If Python3 is readily available, set up your virtual environment by running these commands:
python3 -m venv venv
source venv/bin/activate
You can also use Anaconda for the specific python version.
conda create -n "venv10" python=3.10
conda activate venv10
Pip is the package installer for Python. It comes pre-packaged with Python. This will be used to install our requirements as such:
pip install --upgrade pip
pip install -r requirements.txt
Once installed, behave will be available for testing.
Initialization
Initialize the web service via this command:
streamlit run webapp.py
Once initialized, you may access the tool at http://localhost:8501.
Testing
Running all the tests in this repository is as simple as running this command:
behave
The results of your BDD tests can sometimes be difficult to view in the terminal. To view the tests results in the browser, we can use allure-behave, which was installed by pip during the bootstrapping process.
You will first need to specify behave to generate formatted allure results
behave -f allure_behave.formatter:AllureFormatter -o tests/results/ Finally, to view these formatted results in the browser, enter this command:
allure serve tests/results
Docker Deployment ⤴
To build the docker image the following command may be executed in the project root directory:
docker build -t agg-match-tool .
To deploy the app now we can use the following command. The application should be available in your domain, i.e. http://host:80/
docker run -d -p 80:80 -t agg-match-tool .
To stop the app container, We have to obtain the container id by executing
docker ps -a
Then we have to execute
docker stop $CONTAINER_ID
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