Difference between revisions of "Pharmacolyzer"
Farmakorakel (talk | contribs) (→Examples of use of the Pharmacolyzer REST API) |
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We have coined the verb ''to pharmacolyze'' for the action of the Pharmacolyzer | We have coined the verb ''to pharmacolyze'' for the action of the Pharmacolyzer | ||
| − | === | + | ===Getting access to pharmacolyzis of sensitive data=== |
| − | Patient VCFs are sensitive data, and | + | Patient VCFs are sensitive data, and storage of VCF data and [[Pharmacotyper|pharmacotyping]] are preformed on secure servers. It may also be sensible to run the pharmacolyzer in a facility for sensitive data, and only export the final ''pharmacolysis''. Access to the final PGx analysis could be given through a REST API, and we describe one approach in the section below. |
| − | === | + | ===Example of how access to the Pharmacolyzer through a REST API could look like=== |
| − | We have downloaded a VCF with samples from the [http://grch37.ensembl.org/Homo_sapiens/Tools/DataSlicer?db=core 1000 genomes project]. Four samples from the VCF was then [[Pharmacotyper|pharmacotyped]] and stored in a JSON file called ''merged_patient.json''. Pharmacolysis can be performed for the following drugs and patient samples: | + | We have downloaded a VCF with samples from the [http://grch37.ensembl.org/Homo_sapiens/Tools/DataSlicer?db=core 1000 genomes project]. Four samples from the VCF was then [[Pharmacotyper|pharmacotyped]] and stored in a JSON file called ''merged_patient.json'' which is now accessible to the Pharmacolyzer at pgx.no. Pharmacolysis can be performed for the following drugs and patient samples: |
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For pretty printing, the following can be used: | For pretty printing, the following can be used: | ||
<pre>curl https://www.pgx.no/api/pharmacolyzer -d "patient_name=merged_patient&drugs=azathioprine&samples=NA19461" | python -m json.tool </pre> | <pre>curl https://www.pgx.no/api/pharmacolyzer -d "patient_name=merged_patient&drugs=azathioprine&samples=NA19461" | python -m json.tool </pre> | ||
| + | Note that this is quite slow (20-30 seconds, especially the first query, when the OWL reasoner process is being set up, later queries may become as little as 4-5 seconds, which is still a bit slow for such a simple program) | ||
Latest revision as of 12:50, 28 August 2018
Pharmacolyzer - Personalizing the PGx recommendations
In order to get personalized medication recommendations for a patient that has been sequenced, the Pharmacolyzer does multiple queries to the Pharmacoracle.
The starting point is a JSON file with a representation of the patient VCF in Manchester syntax provided by the Pharmacotyper.
We have coined the verb to pharmacolyze for the action of the Pharmacolyzer
Getting access to pharmacolyzis of sensitive data
Patient VCFs are sensitive data, and storage of VCF data and pharmacotyping are preformed on secure servers. It may also be sensible to run the pharmacolyzer in a facility for sensitive data, and only export the final pharmacolysis. Access to the final PGx analysis could be given through a REST API, and we describe one approach in the section below.
Example of how access to the Pharmacolyzer through a REST API could look like
We have downloaded a VCF with samples from the 1000 genomes project. Four samples from the VCF was then pharmacotyped and stored in a JSON file called merged_patient.json which is now accessible to the Pharmacolyzer at pgx.no. Pharmacolysis can be performed for the following drugs and patient samples:
| Drugs | Samples |
|---|---|
| azathioprine clopidogrel |
NA19461 NA19068 NA20754 NA21137 |
by running commands on the form
curl https://www.pgx.no/api/pharmacolyzer -d "patient_name=merged_patient&drugs=azathioprine&samples=NA19461&samples=NA21137"
from the command line. For pretty printing, the following can be used:
curl https://www.pgx.no/api/pharmacolyzer -d "patient_name=merged_patient&drugs=azathioprine&samples=NA19461" | python -m json.tool
Note that this is quite slow (20-30 seconds, especially the first query, when the OWL reasoner process is being set up, later queries may become as little as 4-5 seconds, which is still a bit slow for such a simple program)
