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Bugfix: Explore command mixed the two adaptor ends together in the dataframe #71

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merged 3 commits into from
Feb 14, 2024
+27 −23
Merged

Bugfix: Explore command mixed the two adaptor ends together in the dataframe #71

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9541207
Bugfix for correct adaptor comparison
alneberg Feb 2, 2024
79fa1f1
Log match requirements
alneberg Feb 2, 2024
87192b6
Remove the logging of inclusion criteria
alneberg Feb 2, 2024
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50 changes: 27 additions & 23 deletions anglerfish/explore/explore.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,32 +76,35 @@ def run_explore(

df = pd.DataFrame.from_dict(aln_dict, orient="index")
nr_good_hits = {}

# Match Insert Match = mim
# The cs string filter is quite strict, requiring 10+ perfect match before insert and 10+ perfect match after insert
# The cg string allows for mismatches within the matching strings but no insertions or deletions
# All cg string matches are also cs string matches (subset) but not vice versa
mim_re_cs = (
r"^cs:Z::[1-9][0-9]*\+([a,c,t,g]*):[1-9][0-9]*$" # Match Insert Match = mim
)
mim_re_cg = r"^cg:Z:([0-9]*)M([0-9]*)I([0-9]*)M$"
df_mim = df[df.cs.str.match(mim_re_cs)]

# Extract the match lengths
match_col_df = df_mim.cg.str.extract(mim_re_cg).rename(
{0: "match_1_len", 1: "insert_len", 2: "match_2_len"}, axis=1
)
match_col_df = match_col_df.astype(
{
"match_1_len": "int32",
"insert_len": "int32",
"match_2_len": "int32",
}
)

df_mim.loc[match_col_df.index, match_col_df.columns] = match_col_df

for adaptor_end_name, adaptor_end in zip(
["i5", "i7"], [adaptor.i5, adaptor.i7]
):
if adaptor_end.has_index():
# Match Insert Match = mim
# The cs string filter is quite strict, requiring 10+ perfect match before insert and 10+ perfect match after insert
# The cg string allows for mismatches within the matching strings but no insertions or deletions
# All cg string matches are also cs string matches (subset) but not vice versa
mim_re_cs = r"^cs:Z::[1-9][0-9]*\+([a,c,t,g]*):[1-9][0-9]*$" # Match Insert Match = mim
mim_re_cg = r"^cg:Z:([0-9]*)M([0-9]*)I([0-9]*)M$"
df_mim = df[df.cs.str.match(mim_re_cs)]

# Extract the match lengths
match_col_df = df_mim.cg.str.extract(mim_re_cg).rename(
{0: "match_1_len", 1: "insert_len", 2: "match_2_len"}, axis=1
)
match_col_df = match_col_df.astype(
{
"match_1_len": "int32",
"insert_len": "int32",
"match_2_len": "int32",
}
)

df_mim.loc[match_col_df.index, match_col_df.columns] = match_col_df

# Alignment thresholds
before_thres = round(
adaptor_end.len_before_index() * good_hit_threshold
Expand All @@ -111,7 +114,8 @@ def run_explore(
insert_thres_high = insert_thres_high

requirements = (
(df_mim["match_1_len"] >= (before_thres))
(df_mim["adapter"] == f"{adaptor.name}_{adaptor_end_name}")
& (df_mim["match_1_len"] >= (before_thres))
& (df_mim["insert_len"] >= insert_thres_low)
& (df_mim["insert_len"] <= insert_thres_high)
& (df_mim["match_2_len"] >= (after_thres))
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