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Patpat is public proteomics dataset search framework that only requires protein identifiers to be passed in to search for relevant datasets.

Project description

Update

  1. Fixed a bug for checking connection with iProX

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:

from patpat import hub
from patpat import mapper
from patpat import 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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