def it_raises_if_both_seq_and_uniprot_ac():
csv_string = """
Name, Seq, UniprotAC
P1, A, P100
"""
with zest.raises(ValueError) as e:
helpers.protein_csv_df(csv_string)
assert "both a Seq and a UniprotAC" in str(e.exception)
def it_raises_if_no_name_and_no_uniprot_ac():
csv_string = """
Seq, Abundance
ABC, 10
"""
with zest.raises(ValueError) as e:
helpers.protein_csv_df(csv_string)
assert "missing a Name column" in str(e.exception)
def it_raises_if_no_seq_nor_uniprot_ac():
csv_string = """
Name, Abundance
A, 10
"""
with zest.raises(ValueError) as e:
helpers.protein_csv_df(csv_string)
assert "missing either a Seq or a UniprotAC" in str(e.exception)
def it_raises_on_duplicate_seqs():
csv_string = """
Name, Seq
P1, ABC
P2, ABC
"""
with zest.raises(ValueError) as e:
helpers.protein_csv_df(csv_string)
assert "duplicate seqs" in str(e.exception)
def it_warns_on_no_seq_from_uniprot():
csv_string = """
UniprotAC
P1
"""
with zest.mock(helpers._protein_csv_warning) as m_warn:
with zest.mock(helpers._uniprot_lookup) as m_lookup:
m_lookup.returns([])
helpers.protein_csv_df(csv_string)
assert m_warn.called_once()
def it_sorts_by_name_if_no_abundance():
csv_string = """
Name, Seq
P2, DEF
P1, ABC
"""
df = helpers.protein_csv_df(csv_string)
assert df.loc[0, "seqstr"] == "ABC" and df.loc[0, "id"] == "P1"
assert df.loc[1, "seqstr"] == "DEF" and df.loc[1, "id"] == "P2"
def it_nans_missing_abundances():
csv_string = """
UniprotAC
P1
"""
with zest.mock(helpers._uniprot_lookup) as m:
m.returns([{"id:": "foo", "seqstr": "ABC"}])
df = helpers.protein_csv_df(csv_string)
assert (df.loc[0, "id"] == "P1" and df.loc[0, "seqstr"] == "ABC"
and np.isnan(df.loc[0, "abundance"]))
def it_imports_ptm():
csv_string = """
Name, Seq, PTM
P1, ABC, 3
P2, DEF, 1;2
P3, GHI,
"""
df = helpers.protein_csv_df(csv_string)
assert df.loc[0, "ptm_locs"] == "3"
assert df.loc[1, "ptm_locs"] == "1;2"
assert df.loc[2, "ptm_locs"] == ""
def it_reverse_sorts_by_abundance():
csv_string = """
Name, Seq, Abundance
P1, ABC, 10
P2, DEF, 100
"""
df = helpers.protein_csv_df(csv_string)
assert (df.loc[0, "seqstr"] == "DEF" and df.loc[0, "id"] == "P2"
and df.loc[0, "abundance"] == 100.0)
assert (df.loc[1, "seqstr"] == "ABC" and df.loc[1, "id"] == "P1"
and df.loc[1, "abundance"] == 10.0)
def protein_csv(self, sources):
"""
Include protein(s) in csv format (Must have a header row with 'Name', 'Seq' and optional
'Abundance', 'UniprotAC', and 'PTM' columns.). May be a local File-path or URL.
"""
for source in sources:
source = helpers.cache_source(
self.cache_folder, source, self.local_sources_tmp_folder
)
proteins_df = helpers.protein_csv_df(source)
self.derived_vals.protein += proteins_df.to_dict("records")
def protein_csv(self, sources):
"""
Include protein(s) in csv format (Must have a header row with 'Name', 'Seq' and optional
'Abundance', 'UniprotAC', and 'PTM' columns.). May be a local File-path or URL.
"""
for source in sources:
source = helpers.cache_source(self.cache_folder, source,
self.local_sources_tmp_folder)
proteins_df = helpers.protein_csv_df(source)
# Handy hack when you need to save the sequences
# This needs to become its own tool at some point
# proteins_df.to_csv("_pro_df.csv")
self.derived_vals.protein += proteins_df.to_dict("records")
def it_accepts_name_and_sequence():
csv_string = """
Name, Seq
P1, ABC
P2, DEF
"""
df = helpers.protein_csv_df(csv_string)
assert df.loc[0, "seqstr"] == "ABC" and df.loc[0, "id"] == "P1"
assert df.loc[1, "seqstr"] == "DEF" and df.loc[1, "id"] == "P2"
def it_defaults_ptm_locs_to_empty_str():
assert df.loc[0, "ptm_locs"] == ""
def it_defaults_abundance_to_nan():
assert np.isnan(df.loc[0, "abundance"])
zest()
def it_warns_on_more_than_one_seq_from_uniprot():
csv_string = """
UniprotAC
P1
"""
with zest.mock(helpers._protein_csv_warning) as m_warn:
with zest.mock(helpers._uniprot_lookup) as m_lookup:
m_lookup.returns([{
"id": "foo",
"seqstr": "123"
}, {
"id": "bar",
"seqstr": "123456"
}])
df = helpers.protein_csv_df(csv_string)
assert len(df) == 1 and df.loc[0, "seqstr"] == "123456"
assert m_warn.called_once()
def it_lookups_uniprot():
csv_string = """
UniprotAC, Abundance
P1, 10
"""
with zest.mock(helpers._uniprot_lookup) as m:
m.returns([{"id:": "foo", "seqstr": "ABC"}])
df = helpers.protein_csv_df(csv_string)
assert df.loc[0, "seqstr"] == "ABC"
def it_uses_uniprot_ac_as_name():
assert df.loc[0, "id"] == "P1"
def it_imports_abundance():
assert df.loc[0, "abundance"] == 10.0
zest()
