Patpat is public proteomics dataset search framework that only requires protein identifiers to be passed in to search for relevant datasets.
Project description
Patpat
Patpat is public proteomics dataset search framework that only requires protein identifiers to be passed in to search for relevant datasets
Base Usage
Load Patpat package and create runtime environment:
import patpat.hub as hub
import patpat.mapper as mapper
import patpat.utility as utility
utility.init()
utility.initiate_uniprot_proteome_catalog()
Directory structure of the runtime environment is as follows:
patpat_env/
|-- logs/
|-- tmp/
|-- result/
|-- proteome/
|-- UP_README_yyyy-mm-dd
Search for the peptide to be searched via the QueryHub
identifier_ = 'P23950'
q = hub.QueryHub()
q.identifier = identifier_
q.simple_query()
Having checked that the corresponding FASTA file for Mus musculus does not exist locally, consider obtaining from UniProt:
Choose local peptide search.
The Mus musculus UP000000589 proteome file was not found locally.
Do you want to download it?(y/n)
Get the search configs:
conf_ = q.get_query_config()
Set up Mappers for MapperHub, search and get results:
mappers_ = [mapper.PrideMapper(), mapper.IProXMapper()]
m = hub.MapperHub(config=conf_,
mappers=mappers_,
)
m.mapping()
result_ = m.export()
Result files store in patpat_envs/result/<task_uuid>
, you can find <task_uuid>
by m.config
In its current version, Patpat supports both PRIDE and iProX databases. In addition, Patpat is an extensible framework and users are encouraged to extend it with databases of interest to Patpat or to build their processes.
For more information, see GitHub (https://github.com/henry-leo/Patpat).
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