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[FIX] Decoding ontology in PeptideIdentification df conversion #5659

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merged 8 commits into from Nov 18, 2021
Merged

[FIX] Decoding ontology in PeptideIdentification df conversion #5659

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5bea56c
fix tuple creation
axelwalter Nov 15, 2021
ba16bbc
add pep evidence export
axelwalter Nov 15, 2021
0a1ffe2
update test
axelwalter Nov 15, 2021
c2db89d
add pep evidence concatenation test
axelwalter Nov 16, 2021
1faf378
change dtype for pep evidences to U1000
axelwalter Nov 16, 2021
c96a601
fix error while decoding ontology
axelwalter Nov 17, 2021
e61533a
simple test without decode_ontology
axelwalter Nov 17, 2021
3d5ca32
Merge branch 'develop' into feature/pep-evidences-df
axelwalter Nov 17, 2021
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13 changes: 8 additions & 5 deletions src/pyOpenMS/pyopenms/dataframes.py
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Expand Up @@ -288,11 +288,14 @@ def get_key(val):
return key
dmv = [default_missing_values[get_key(t)] for t in types]

decodedMVs = [m.decode("utf-8") for m in metavals] if decode_ontology else metavals
cv = ControlledVocabulary()
cv.loadFromOBO("psims", File.getOpenMSDataPath() + "/CV/psi-ms.obo")
clearMVs = [cv.getTerm(m).name if m.startswith("MS:") else m for m in decodedMVs]
#cols = ["id", "RT", "mz", "score", "charge"] + decodedMVs
decodedMVs = [m.decode("utf-8") for m in metavals]
if decode_ontology:
cv = ControlledVocabulary()
cv.loadFromOBO("psims", File.getOpenMSDataPath() + "/CV/psi-ms.obo")
clearMVs = [cv.getTerm(m).name if m.startswith("MS:") else m for m in decodedMVs]
else:
clearMVs = decodedMVs

clearcols = ["id", "RT", "mz", mainscorename, "charge", "protein_accession", "start", "end"] + clearMVs
coltypes = ['U100', 'f', 'f', 'f', 'i','U1000', 'U1000', 'U1000'] + types
dt = list(zip(clearcols, coltypes))
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1 change: 1 addition & 0 deletions src/pyOpenMS/tests/unittests/test000.py
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Expand Up @@ -2278,6 +2278,7 @@ def test_peptide_identifications_to_df():
peps.append(p1)

assert pyopenms.peptide_identifications_to_df(peps).shape == (2,10)
assert pyopenms.peptide_identifications_to_df(peps, decode_ontology=False).shape == (2,10)
assert pyopenms.peptide_identifications_to_df(peps)['protein_accession'][0] == 'sp|Accession1,sp|Accession2'
assert pyopenms.peptide_identifications_to_df(peps, export_unidentified=False).shape == (1,10)

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