3. Query functions ¶

Contents

3.1. Before you query ¶

3.1.1. 1. You can use % as a wildcard.¶

import pyhgnc
query = pyhgnc.query()

# exact search
query.hgnc(name='amyloid beta precursor protein')

# starts with 'amyloid beta'
query.hgnc(name='amyloid beta %')

# ends with 'precursor protein'
query.hgnc(name='% precursor protein')

# contains 'precursor'
query.hgnc(name='%precursor%')

3.1.2. 2. limit to restrict number of results ¶

import pyhgnc
query = pyhgnc.query()

query.hgnc(limit=10)

Use an offset by paring a tuple (page_number, number_of_results_per_page) to the parameter limit.

page_number starts with 0!

import pyhgnc
query = pyhgnc.query()

# first page with 3 results (every page have 3 results)
query.hgnc(limit=(0,3))
# fourth page with 10 results (every page have 10 results)
query.hgnc(limit=(4,10))

3.1.3. 3. Return `pandas.DataFrame` as result¶

This is very useful if you want to profit from amazing pandas functions.

import pyhgnc
query = pyhgnc.query()

query.hgnc(as_df=True)

3.1.4. 4. show all columns as dict ¶

import pyhgnc
query = pyhgnc.query()

first_entry = query.hgnc(limit=1)[0]
first_entry.to_dict()

3.1.5. 5. Return single values with key name ¶

import pyhgnc
query = pyhgnc.query()

query.hgnc(name='%kinase')[0].name

3.1.6. 6. Access to the linked data models (1-n, n-m)¶

From results of pyhgnc.query().hgnc() you can access

alias_symbols
alias_names
rgds
omims
ccdss
lsdbs
orthology_predictions
enzymes
gene_families
refseq_accessions
mgds
uniprots
pubmeds
enas

import pyhgnc
query = pyhgnc.query()

r = query.hgnc(limit=1)[0]

r.alias_symbols
r.alias_names
r.rgds
r.omims
r.ccdss
r.lsdbs
r.orthology_predictions
r.enzymes
r.gene_families
r.refseq_accessions
r.mgds
r.uniprots
r.pubmeds
r.enas

But for example from pyhgnc.query().uniprot() you can go back to hgnc

import pyhgnc
query = pyhgnc.query()

uniprot = query.uniprot(uniprotid='Q9BTE6')[0]
uniprot.hgncs
# [AARSD1, PTGES3L-AARSD1]
# following is crazy but possible, again go back to ec_number
uniprot.hgncs[0].uniprots
# [Q9BTE6]

3.1.7. 7. HGNC identifier and symbol is available in all methods ¶

Hint

In all query functions (except hgnc) you have the parameters - hgnc_identifier - hgnc_symbol even it is not part of the model.

import pyhgnc
query = pyhgnc.query()

query.alias_symbol(hgnc_identifier=620)
# [AD1]
query.alias_symbol(hgnc_symbol='APP')
# [AD1]

3.2. hgnc ¶

import pyhgnc
query = pyhgnc.query()

query.hgnc(entrez=503538)

Check documentation of pyhgnc.manager.query.QueryManager.hgnc() for all available parameters.

3.3. orthology_prediction ¶

import pyhgnc
query = pyhgnc.query()

query.orthology_prediction(ortholog_species=10090, hgnc_symbol='APP')
# [10090: amyloid beta (A4) precursor protein: App]

Check documentation of pyhgnc.manager.query.QueryManager.orthology_prediction() for all available parameters.

3.4. alias_symbol ¶

import pyhgnc
query = pyhgnc.query()

result = query.alias_symbol(alias_symbol='AD1')[0]
result.hgnc
# APP

Check documentation of pyhgnc.manager.query.QueryManager.alias_symbol() for all available parameters.

3.5. alias_name ¶

import pyhgnc
query = pyhgnc.query()

result = query.alias_name(alias_name='peptidase nexin-II')[0]
result.hgnc.name
# 'amyloid beta precursor protein'

Check documentation of pyhgnc.manager.query.QueryManager.alias_name() for all available parameters.

3.6. gene_family ¶

import pyhgnc
query = pyhgnc.query()

    result = query.gene_family(family_name='Parkinson%')[0]
result
# 'Parkinson disease associated genes'
result.hgncs
# [ATP13A2, EIF4G1, FBXO7, HTRA2, LRRK2, PARK3, PARK7, PARK10, PARK11, PARK12, PARK16, PINK1,\
# PLA2G6, PRKN, SNCA, UCHL1, VPS35]

Check documentation of pyhgnc.manager.query.QueryManager.gene_family() for all available parameters.

3.7. ref_seq ¶

import pyhgnc
query = pyhgnc.query()

query.ref_seq(hgnc_symbol='APP')
# [NM_000484]

Check documentation of pyhgnc.manager.query.QueryManager.ref_seq() for all available parameters.

3.8. rgd ¶

import pyhgnc
query = pyhgnc.query()

query.rgd(rgdid=2139)[0].hgncs
# [APP]

Check documentation of pyhgnc.manager.query.QueryManager.rgd() for all available parameters.

3.9. omim ¶

import pyhgnc
query = pyhgnc.query()

query.omim(omimid=104760)[0].hgnc.name
# 'amyloid beta precursor protein'

Check documentation of pyhgnc.manager.query.QueryManager.omim() for all available parameters.

3.10. mgd ¶

import pyhgnc
query = pyhgnc.query()

query.mgd(mgdid=88059)[0].hgncs
# [APP]

Check documentation of pyhgnc.manager.query.QueryManager.mgd() for all available parameters.

3.11. uniprot ¶

import pyhgnc
query = pyhgnc.query()

query.uniprot(uniprotid='P05067')[0].hgncs
# [APP]

Check documentation of pyhgnc.manager.query.QueryManager.uniprot() for all available parameters.

3.12. ccds ¶

import pyhgnc
query = pyhgnc.query()

query.ccds(ccdsid='CCDS13576')[0].hgnc
# APP

Check documentation of pyhgnc.manager.query.QueryManager.ccds() for all available parameters.

3.13. pubmed ¶

import pyhgnc
query = pyhgnc.query()

query.pubmed(hgnc_symbol='A1CF')
# [11815617, 11072063]

Check documentation of pyhgnc.manager.query.QueryManager.pubmed() for all available parameters.

3.14. ena ¶

import pyhgnc
query = pyhgnc.query()

query.ena(hgnc_identifier=620)
# [AD1]

Check documentation of pyhgnc.manager.query.QueryManager.ena() for all available parameters.

3.15. enzyme ¶

import pyhgnc
query = pyhgnc.query()

query.enzyme(hgnc_symbol='PRKCA')
# [2.7.11.1]

Check documentation of pyhgnc.manager.query.QueryManager.enzyme() for all available parameters.

3.16. lsdb ¶

import pyhgnc
query = pyhgnc.query()

query.lsdb(hgnc_symbol='APP')
# [Alzheimer Disease & Frontotemporal Dementia Mutation Database]

Check documentation of pyhgnc.manager.query.QueryManager.lsdb() for all available parameters.

3.1.3. 3. Return pandas.DataFrame as result¶

3.1.3. 3. Return `pandas.DataFrame` as result¶