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Handle empty fastqc reports #598

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Handle empty fastqc reports #598

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21 changes: 13 additions & 8 deletions sunbeam/workflow/scripts/fastqc_report.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,17 +2,22 @@
from typing import TextIO


def f(log: TextIO):
import pandas
from sunbeam.bfx.reports import parse_fastqc_quality
def f(log: TextIO):
import pandas
from sunbeam.bfx.reports import parse_fastqc_quality

input_reports = snakemake.input.reports # type: ignore
output_report = snakemake.output.report # type: ignore

quality_list = [parse_fastqc_quality(file) for file in input_reports]
quality_list = [qr for qr in quality_list if qr is not None]
quality_table = pandas.concat(quality_list, axis=1).transpose()
quality_table.to_csv(output_report, sep="\t", index_label="Samples")

quality_list = [parse_fastqc_quality(file) for file in input_reports]
quality_list = [qr for qr in quality_list if qr is not None]
if len(quality_list) == 0:
log.write("No per-base sequence quality data found; writing empty report.\n")
pandas.DataFrame().to_csv(output_report, sep="\t", index_label="Samples")
return
Comment on lines +14 to +17

Copilot AI Dec 2, 2025

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The new empty report handling logic lacks test coverage. Consider adding unit tests to verify:

  1. The behavior when all input reports return None from parse_fastqc_quality (empty quality_list)
  2. That an empty DataFrame is correctly written to the output file
  3. That the appropriate log message is written

Similar workflow scripts like preprocess_report.py have comprehensive unit tests in tests/unit/test_preprocess_report.py. Consider adding a tests/unit/test_fastqc_report.py file with tests for this new functionality.

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quality_table = pandas.concat(quality_list, axis=1).transpose()
quality_table.to_csv(output_report, sep="\t", index_label="Samples")


log_f = snakemake.log[0] # type: ignore
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