A library for making a local copy of the Pathosystems Resource Integration Center's genome annotations in a relational database.
Some time ago I thought it'd be a great idea to include the annotations derived from PATRIC in my project. Later I realized that the only programmatic method for accessing their data was to use their FTP server to bulk download the relevant files and parse them.
This little library is an attempt to make the process of consuming that data simpler, and provide a simple relational scheme for representing that data once it is consumed. It uses SQLAlchemy's ORM to structure things.
It currently is hard-coded to use SQLite, however this could easily be changed to use an arbitrary database connection URI.
from patric_mirror import mirror, make_session, Genome, Feature, Pathway
db_file = "path/to/storage.db"
mirror(db_file) # mirror all annotations into this database
# Later, looking for metabolism features
session = make_session(db_file)
balneola_vulgaris_metabolism_features = session.query(Feature).filter(Feature.accession == "AQXH01000001").join(
Pathway).filter(Pathway.description.like("%metabolism%")).all()
# Elsewhere, looking for features mapped by sequencing of this chromosome/genome
from collectons import Counter
mapped_coordinates = get_mapped_coordinates_from_sam_file()
mapped_go_terms = Counter()
for read_start, read_end in mapped_coordinates:
features = session.query(Feature).filter(
Feature.accession == "AQXH01000001", Feature.spans(read_start) or Feature.spans(read_end)).all()
for feature in features:
for go_term in feature.go_terms:
mapped_go_terms[go_term.description] += 1If you use data derived from PATRIC, please be sure to cite the relevant publication below:
Note
Wattam, A.R., D. Abraham, O. Dalay, T.L. Disz, T. Driscoll, J.L. Gabbard, J.J. Gillespie, R. Gough, D. Hix, R. Kenyon, D. Machi, C. Mao, E.K. Nordberg, R. Olson, R. Overbeek, G.D. Pusch, M. Shukla, J. Schulman, R.L. Stevens, D.E. Sullivan, V. Vonstein, A. Warren, R. Will, M.J.C. Wilson, H. Seung Yoo, C. Zhang, Y. Zhang, B.W. Sobral (2014). “PATRIC, the bacterial bioinformatics database and analysis resource.” Nucl Acids Res 42 (D1): D581-D591. doi:10.1093/nar/gkt1099. PMID: 24225323.