The CovCheck analysis computes a personal genome report indicating 'risk of severe symptoms' (CFR) from COVID-19 infection.
The risk analysis is based on published, peer-reviewed studies: https://www.covid19hg.org/publications/
Personal genome data and age (if provided) is read from a simple 'genome file' in JSON format.
Note that this analyis is work in progress!!!
To install, pull from git:
git@github.com:Geromics/covcheck.git
change to the appropriate directory:
cd covcheck
and run the code:
python3 covid_genetic_check.py -h
usage: check.py [-h] [--version] [--verbose] infile [outfile]
Score an individual.
positional arguments:
infile JSON format file containing individual data
outfile JSON format results file (default: <stdout>)
optional arguments:
-h, --help show this help message and exit
--version show program's version number and exit
--verbose, -v
The only formal requirements (requirements.txt) are for testing:
pip install -r requirements.txt
which is done by:
python3 -m pytest -v .
Note, project dependncies are not managed by a high level tool such as flit, poetry or Pipenv.
The analysis of risk with age is based on data from here:
and has been done with help from:
The genome report is currently based on the analysis in this preprint: https://www.researchsquare.com/article/rs-37798/v1
Notes from the preprint...
##reference=GRCh38.p12
chr21 41480570 rs12329760 C T . . .
chr21 41507982 rs75603675 C A . . .
rs12329760, TMPRSS2(-), V197M, C->T (G->A, V[GTG] -> M[ATG])
C is the risk allele, T is 'protective'
rs75603675, TMPRSS2(-), G008V, C->A (G->T, G[GGT] -> V[GTT])
A is the risk allele, C is 'protective'
Spearman’s correlation with COVID-19 CFR:
ρ = -0.464, P = 0.0157 for V197M C->T (G->A)
ρ = +0.713, P = 0.0018 for G008V C->A (G->T)
The higher the score, the greater your genetic risk of severe
COVID-19 infection.
- QCovid® risk calculator
- The Association of Local Authority Medical Advisors (ALAMA), COVID-AGE
- Charlson Comorbidity Index
- GenOMICC COVID-19 Study
- From Basic Science to Clinical Application of Polygenic Risk Scores: A Primer.
- Towards clinical utility of polygenic risk scores.
- Genetic susceptibility of COVID-19: a systematic review of current evidence
- Mapping the human genetic architecture of COVID-19
- Identification of LZTFL1 as a candidate effector gene at a COVID-19 risk locus
- The major genetic risk factor for severe COVID-19 is inherited from Neanderthals
- Genetic mechanisms of critical illness in COVID-19
- The quest to find genes that drive severe COVID
- A catalog of associations between rare coding variants and COVID-19 outcomes
A common pattern to mark an unfinished code is to raise a
NotImplementedError that is noticed at runtime:
@classmethod
def from_api(cls, url):
raise NotImplementedError # TODO
TODO: Use a few tools to automatically take care of code formatting (black), flag style-related problems (flake8), as well as warn about potential bugs (pylint).