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Update/export scored report #162

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Merged
singjc merged 2 commits into from
Oct 9, 2025
Merged

Update/export scored report #162

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f53789f
feat: implement export functionality for scored reports with parquet …
singjc Oct 9, 2025
7684484
fix: ensure score_ipf_qvalue is checked for NaN before filtering
singjc Oct 9, 2025
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43 changes: 15 additions & 28 deletions pyprophet/export/export_report.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,10 @@
import sqlite3
import pandas as pd


from .._config import ExportIOConfig
from ..report import post_scoring_report
from ..io.dispatcher import ReaderDispatcher
from ..io.util import get_parquet_column_names
from ..io.util import check_sqlite_table
from ..report import plot_scores
Expand Down Expand Up @@ -130,35 +133,19 @@ def export_scored_report(
The format of the scoring report, either 'osw' or 'parquet'. Default is 'osw'.
"""

cols_infile = get_parquet_column_names(infile)

select_cols = [
"RUN_ID",
"PROTEIN_ID",
"PEPTIDE_ID",
"PRECURSOR_ID",
"PRECURSOR_DECOY",
"FEATURE_MS2_AREA_INTENSITY",
"SCORE_MS2_SCORE",
"SCORE_MS2_PEAK_GROUP_RANK",
"SCORE_MS2_Q_VALUE",
"SCORE_PEPTIDE_GLOBAL_SCORE",
"SCORE_PEPTIDE_GLOBAL_Q_VALUE",
"SCORE_PEPTIDE_EXPERIMENT_WIDE_SCORE",
"SCORE_PEPTIDE_EXPERIMENT_WIDE_Q_VALUE",
"SCORE_PEPTIDE_RUN_SPECIFIC_SCORE",
"SCORE_PEPTIDE_RUN_SPECIFIC_Q_VALUE",
"SCORE_PROTEIN_GLOBAL_SCORE",
"SCORE_PROTEIN_GLOBAL_Q_VALUE",
"SCORE_PROTEIN_EXPERIMENT_WIDE_SCORE",
"SCORE_PROTEIN_EXPERIMENT_WIDE_Q_VALUE",
"SCORE_IPF_QVALUE",
]
config = ExportIOConfig(
infile=infile,
outfile=outfile,
subsample_ratio=1.0, # not used for export/report paths
level="export",
context="export_scored_report",
# no need to set export_format for this utility
)

# Filter select cols based on available columns in the input file
select_cols = [col for col in select_cols if col in cols_infile]
# Get the right reader for the detected file type & context.
reader = ReaderDispatcher.get_reader(config)

# Load the input data
df = pd.read_parquet(infile, columns=select_cols)
# Read once (works for OSW or Parquet via their respective readers).
df = reader.read()

post_scoring_report(df, outfile)
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