Check is a valid sample sheet use the extensive validation [CW-7210]
This commit is contained in:
Natalia Garcia
parent
74cbe196b2
commit
0ae50f9a35
@ -69,7 +69,7 @@ docker-run:
|
||||
- MATRIX_NAME: [
|
||||
"int_discover_dna", "int_fixed_rna", "int_de_control_vs_control",
|
||||
"smoke_discover", "smoke_fixed", "smoke_direct_rna", "smoke_de",
|
||||
"mouse_de_0countquant", "mods_bigwig_igv"
|
||||
"mouse_de_0countquant", "mods_bigwig_igv", "mismatch-sample-alias"
|
||||
]
|
||||
rules:
|
||||
# NOTE As we're overriding the rules block for the included docker-run
|
||||
@ -173,6 +173,13 @@ docker-run:
|
||||
test -f ${CI_PROJECT_NAME}/de_analysis/condition_treated_vs_control/results_dge.tsv &&
|
||||
test -f ${CI_PROJECT_NAME}/de_analysis/condition_treated_vs_control/results_dtu_transcript.tsv &&
|
||||
[ "$(find ${CI_PROJECT_NAME}/samples -type f -name 'gene_counts.tsv' | wc -l)" -eq 4 ]
|
||||
- if: $MATRIX_NAME == "mismatch-sample-alias"
|
||||
variables:
|
||||
NF_BEFORE_SCRIPT: ":"
|
||||
NF_WORKFLOW_OPTS: "--fastq test_data/smoke/de/barcode01/reads.fastq --sample_sheet test_data/smoke/sample_sheet_de.csv --ref_genome test_data/smoke/reference.fa --ref_annotation test_data/smoke/annotation.gtf"
|
||||
ASSERT_NEXTFLOW_FAILURE: "1"
|
||||
AFTER_NEXTFLOW_CMD: >
|
||||
grep -F "Sample alias 'reads' was not found in the sample_sheet alias column." .nextflow.log
|
||||
# Tests a common error when there are 0 annotation counts for a chunk
|
||||
- if: $MATRIX_NAME == "mouse_de_0countquant"
|
||||
variables:
|
||||
|
||||
@ -1,126 +0,0 @@
|
||||
"""Validate DE/DTU sample sheet settings."""
|
||||
|
||||
from collections import Counter
|
||||
import csv
|
||||
import sys
|
||||
|
||||
from .util import get_named_logger, wf_parser # noqa: ABS101
|
||||
|
||||
|
||||
def _split_covariates(value):
|
||||
if not value:
|
||||
return []
|
||||
return [part.strip() for part in value.split(",") if part.strip()]
|
||||
|
||||
|
||||
def main(args):
|
||||
"""Validate sample sheet content for DE/DTU."""
|
||||
logger = get_named_logger("checkDesign")
|
||||
covariates = _split_covariates(args.covariates)
|
||||
with open(args.sample_sheet, "r", newline="") as handle:
|
||||
reader = csv.DictReader(handle)
|
||||
if reader.fieldnames is None:
|
||||
sys.exit("Sample sheet is empty.")
|
||||
fieldnames = set(reader.fieldnames)
|
||||
required = {"alias", args.condition_column}
|
||||
missing = sorted(required - fieldnames)
|
||||
if missing:
|
||||
sys.exit(
|
||||
"Sample sheet is missing required columns: "
|
||||
+ ", ".join(missing)
|
||||
)
|
||||
|
||||
missing_covariates = [name for name in covariates if name not in fieldnames]
|
||||
if missing_covariates:
|
||||
sys.exit(
|
||||
"Sample sheet is missing requested covariate columns: "
|
||||
+ ", ".join(missing_covariates)
|
||||
)
|
||||
|
||||
aliases = []
|
||||
levels = Counter()
|
||||
for row in reader:
|
||||
alias = row.get("alias", "").strip()
|
||||
if not alias:
|
||||
sys.exit("Sample sheet contains a row with an empty alias value.")
|
||||
aliases.append(alias)
|
||||
|
||||
value = row.get(args.condition_column, "").strip()
|
||||
if not value:
|
||||
sys.exit(
|
||||
f"Sample sheet contains a row with an empty "
|
||||
f"'{args.condition_column}' value."
|
||||
)
|
||||
levels[value] += 1
|
||||
|
||||
for covariate in covariates:
|
||||
if not row.get(covariate, "").strip():
|
||||
sys.exit(
|
||||
f"Sample sheet contains an empty value in covariate column "
|
||||
f"'{covariate}'."
|
||||
)
|
||||
|
||||
duplicate_aliases = [
|
||||
alias for alias, count in Counter(aliases).items() if count > 1
|
||||
]
|
||||
if duplicate_aliases:
|
||||
sys.exit(
|
||||
"Sample sheet aliases must be unique. Duplicates: "
|
||||
+ ", ".join(sorted(duplicate_aliases))
|
||||
)
|
||||
|
||||
if len(levels) < 2:
|
||||
sys.exit(
|
||||
f"The condition column '{args.condition_column}' must contain at "
|
||||
"least two levels."
|
||||
)
|
||||
|
||||
reference_level = args.reference_level
|
||||
if not reference_level:
|
||||
if "control" in levels:
|
||||
reference_level = "control"
|
||||
else:
|
||||
sys.exit(
|
||||
"Provide --reference_level when the condition column does not "
|
||||
"contain 'control'."
|
||||
)
|
||||
|
||||
if reference_level not in levels:
|
||||
sys.exit(
|
||||
f"Reference level '{reference_level}' was absent from "
|
||||
f"'{args.condition_column}'."
|
||||
)
|
||||
|
||||
underpowered = [level for level, count in levels.items() if count < 2]
|
||||
if underpowered:
|
||||
sys.exit(
|
||||
"Each condition level must contain at least two samples. "
|
||||
"Levels with too few samples: "
|
||||
+ ", ".join(sorted(underpowered))
|
||||
)
|
||||
|
||||
logger.info(
|
||||
"Validated sample sheet %s using condition column '%s' with reference '%s'.",
|
||||
args.sample_sheet,
|
||||
args.condition_column,
|
||||
reference_level,
|
||||
)
|
||||
|
||||
|
||||
def argparser():
|
||||
"""Argument parser for the validation entry point."""
|
||||
parser = wf_parser("check_experiment_design")
|
||||
parser.add_argument("--sample_sheet", required=True, help="Sample sheet CSV.")
|
||||
parser.add_argument(
|
||||
"--condition_column", default="condition",
|
||||
help="Primary biological variable column."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--covariates", default=None,
|
||||
help="Comma-separated nuisance covariates."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--reference_level", default=None,
|
||||
help="Reference level of the primary condition column."
|
||||
)
|
||||
return parser
|
||||
@ -1,72 +0,0 @@
|
||||
"""Tests for DE/DTU design validation."""
|
||||
|
||||
import pytest
|
||||
from workflow_glue import check_experiment_design
|
||||
|
||||
|
||||
def _write(path, text):
|
||||
path.write_text(text, encoding="utf-8")
|
||||
return path
|
||||
|
||||
|
||||
def _args(*argv):
|
||||
return check_experiment_design.argparser().parse_args(list(argv))
|
||||
|
||||
|
||||
def test_split_covariates_trims_and_drops_empty_values():
|
||||
"""Covariates should be normalised into a clean list."""
|
||||
assert check_experiment_design._split_covariates(
|
||||
" batch, sex ,, site "
|
||||
) == ["batch", "sex", "site"]
|
||||
|
||||
|
||||
def test_main_accepts_valid_design(tmp_path):
|
||||
"""A balanced two-condition sample sheet should validate cleanly."""
|
||||
sample_sheet = _write(
|
||||
tmp_path / "sample_sheet.csv",
|
||||
(
|
||||
"alias,condition,batch\n"
|
||||
"control_rep1,control,b1\n"
|
||||
"control_rep2,control,b2\n"
|
||||
"treated_rep1,treated,b1\n"
|
||||
"treated_rep2,treated,b2\n"
|
||||
),
|
||||
)
|
||||
|
||||
check_experiment_design.main(
|
||||
_args("--sample_sheet", str(sample_sheet), "--covariates", "batch")
|
||||
)
|
||||
|
||||
|
||||
def test_main_rejects_duplicate_aliases(tmp_path):
|
||||
"""Duplicate aliases should fail validation."""
|
||||
sample_sheet = _write(
|
||||
tmp_path / "sample_sheet.csv",
|
||||
(
|
||||
"alias,condition\n"
|
||||
"rep1,control\n"
|
||||
"rep1,control\n"
|
||||
"rep3,treated\n"
|
||||
"rep4,treated\n"
|
||||
),
|
||||
)
|
||||
|
||||
with pytest.raises(SystemExit, match="aliases must be unique"):
|
||||
check_experiment_design.main(_args("--sample_sheet", str(sample_sheet)))
|
||||
|
||||
|
||||
def test_main_requires_reference_level_when_control_is_absent(tmp_path):
|
||||
"""Non-control condition labels require an explicit reference level."""
|
||||
sample_sheet = _write(
|
||||
tmp_path / "sample_sheet.csv",
|
||||
(
|
||||
"alias,condition\n"
|
||||
"rep1,baseline\n"
|
||||
"rep2,baseline\n"
|
||||
"rep3,treated\n"
|
||||
"rep4,treated\n"
|
||||
),
|
||||
)
|
||||
|
||||
with pytest.raises(SystemExit, match="Provide --reference_level"):
|
||||
check_experiment_design.main(_args("--sample_sheet", str(sample_sheet)))
|
||||
481
bin/workflow_glue/tests/common/test_check_sample_sheet.py
Normal file
481
bin/workflow_glue/tests/common/test_check_sample_sheet.py
Normal file
@ -0,0 +1,481 @@
|
||||
"""Test check_sample_sheet.py."""
|
||||
|
||||
import json
|
||||
|
||||
import pytest
|
||||
from workflow_glue.wfg_helpers import check_sample_sheet
|
||||
from workflow_glue.wfg_helpers.validators.wf import _validate_r_formula_names
|
||||
|
||||
|
||||
def _run_check_sample_sheet(sample_sheet_path, params_json, capsys):
|
||||
"""Run sample-sheet validation and return captured stdout."""
|
||||
args = [str(sample_sheet_path), str(params_json), "--no_barcode"]
|
||||
parsed_args = check_sample_sheet.argparser().parse_args(args)
|
||||
|
||||
try:
|
||||
check_sample_sheet.main(parsed_args)
|
||||
except SystemExit:
|
||||
pass
|
||||
|
||||
out, _ = capsys.readouterr()
|
||||
return out
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"names",
|
||||
[
|
||||
[
|
||||
"condition", "batch_1", "site.2",
|
||||
"S01", "a1", "sample_group",
|
||||
"01", "1batch", "2.site-3"
|
||||
],
|
||||
],
|
||||
)
|
||||
def test_validate_r_formula_names_accepts_valid_names(names):
|
||||
"""R formula names accept alnum-led names with safe punctuation."""
|
||||
_validate_r_formula_names(names)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"names",
|
||||
[
|
||||
["_condition"],
|
||||
["condition 1"],
|
||||
["size;batch"],
|
||||
["size:batch"],
|
||||
["size|batch"],
|
||||
["sueño"],
|
||||
[""]
|
||||
],
|
||||
)
|
||||
def test_validate_r_formula_names_rejects_invalid_names(names):
|
||||
"""Invalid R formula names should raise a validation error."""
|
||||
with pytest.raises(ValueError):
|
||||
_validate_r_formula_names(names)
|
||||
|
||||
|
||||
def test_check_sample_sheet_skips_condition_check_without_condition_column_param(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Test that condition checks are skipped without the param."""
|
||||
# This would fail (as there is no enough replicates)
|
||||
# but in this case is ok as de_analysis is not enabled
|
||||
sample_sheet_path = tmp_path / "sample_sheet_condition_counts.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,condition\n"
|
||||
"test_name1,condition1\n"
|
||||
"test_name2,condition2\n"
|
||||
"test_name3,condition2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
# condition has a default from the nextflow schema
|
||||
params_json.write_text(
|
||||
json.dumps({"de_analysis": False, "condition_column": "condition"})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out == ""
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_condition_with_single_sample_when_param_present(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Test that each condition must have at least two samples when DE is enabled."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_condition_counts.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition\n"
|
||||
"test_name1,test_sample,condition1\n"
|
||||
"test_name2,positive_control,condition2\n"
|
||||
"test_name3,negative_control,condition2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({"de_analysis": True, "condition_column": "condition"})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith(
|
||||
"Condition must have at least 2 samples: condition1 "
|
||||
"(column: condition)"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_requires_at_least_two_condition_levels(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""DE-enabled sample sheets must contain at least two condition levels."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_single_condition_level.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition\n"
|
||||
"test_name1,test_sample,condition1\n"
|
||||
"test_name2,positive_control,condition1\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({"de_analysis": True, "condition_column": "condition"})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith(
|
||||
"Condition column must contain at least 2 condition levels "
|
||||
"(column: condition)"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_missing_condition_values(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Sample sheets must not contain empty condition cells."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_missing_condition_value.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition\n"
|
||||
"test_name1,test_sample,\n"
|
||||
"test_name2,positive_control,treated\n"
|
||||
"test_name3,negative_control,treated\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({"de_analysis": True, "condition_column": "condition"})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith(
|
||||
"Condition column must not contain missing or empty values "
|
||||
"(column: condition, line: 1)"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_requires_condition_column_when_param_present(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Configured condition columns must exist when DE is enabled."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_missing_condition.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,batch\n"
|
||||
"test_name1,b1\n"
|
||||
"test_name2,b2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({"de_analysis": True, "condition_column": "condition"})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith(
|
||||
"Sample sheet must contain the 'condition' column. "
|
||||
"(column: condition)"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_requires_covariate_columns_when_present(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Check covariate columns exist when provided and DE is enabled."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_missing_covariate.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,condition\n"
|
||||
"test_name1,control\n"
|
||||
"test_name2,control\n"
|
||||
"test_name3,treated\n"
|
||||
"test_name4,treated\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith("Missing covariate columns: batch, site")
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_missing_covariate_values(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Configured covariates must have a value in each row when DE is enabled."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_missing_covariate_value.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,condition,batch,site\n"
|
||||
"test_name1,control,,s1\n"
|
||||
"test_name2,control,b1,s2\n"
|
||||
"test_name3,treated,b2,s1\n"
|
||||
"test_name4,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith(
|
||||
"Covariate column must not contain missing or empty values "
|
||||
"(column: batch, line: 1)"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_unsafe_covariate_values(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Configured covariate values must use safe contrast/design characters."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_invalid_covariate_value.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,condition,good-batch,site\n"
|
||||
"test_name1,control,b1,s1\n"
|
||||
"test_name2,control,b2,s2\n"
|
||||
"test_name3,treated,b 1,s1\n"
|
||||
"test_name4,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "good-batch,site",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith(
|
||||
"Covariate value names must be safe for R formulas. "
|
||||
"Invalid names: b 1. Names must start with a letter or number and "
|
||||
"contain only letters, numbers, underscores, dots, and hyphens. "
|
||||
"(column: good-batch, line: 3)"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_unsafe_column_names(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Configured DE condition and covariate column names may include hyphens."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_invalid_design_name.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,condition-column,bad covariate\n"
|
||||
"test_name1,control,b1\n"
|
||||
"test_name2,control,b2\n"
|
||||
"test_name3,treated,b1\n"
|
||||
"test_name4,treated,b2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition-column",
|
||||
"covariates": "bad covariate",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
assert out.startswith(
|
||||
"Covariate column names must be safe for R formulas. "
|
||||
"Invalid names: bad covariate. Names must start with a letter or "
|
||||
"number and contain only letters, numbers, underscores, dots, and "
|
||||
"hyphens."
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_unsafe_condition_values(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Condition values must be safe for contrast output paths."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_invalid_condition_value.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition,batch,site\n"
|
||||
"test_name1,test_sample,control/group,b1,s1\n"
|
||||
"test_name2,positive_control,control/group,b1,s2\n"
|
||||
"test_name3,test_sample,treated,b2,s1\n"
|
||||
"test_name4,negative_control,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.splitlines() == [
|
||||
"Condition value names must be safe for R formulas. "
|
||||
"Invalid names: control/group. Names must start with a letter or "
|
||||
"number and contain only letters, numbers, underscores, dots, and "
|
||||
"hyphens. (column: condition, line: 1)",
|
||||
"Condition value names must be safe for R formulas. "
|
||||
"Invalid names: control/group. Names must start with a letter or "
|
||||
"number and contain only letters, numbers, underscores, dots, and "
|
||||
"hyphens. (column: condition, line: 2)",
|
||||
]
|
||||
|
||||
|
||||
def test_check_sample_sheet_accepts_control_as_default_reference_level(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Control is accepted as the default reference level when present."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_reference_control.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition,batch,site\n"
|
||||
"test_name1,test_sample,control,b1,s1\n"
|
||||
"test_name2,positive_control,control,b1,s2\n"
|
||||
"test_name3,test_sample,treated,b2,s1\n"
|
||||
"test_name4,negative_control,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out == ""
|
||||
|
||||
|
||||
def test_check_sample_sheet_requires_reference_level_without_control(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""A non-control design requires an explicit reference level."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_missing_reference.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition,batch,site\n"
|
||||
"test_name1,test_sample,baseline,b1,s1\n"
|
||||
"test_name2,positive_control,baseline,b1,s2\n"
|
||||
"test_name3,test_sample,treated,b2,s1\n"
|
||||
"test_name4,negative_control,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
assert out == (
|
||||
"Provide --reference_level when the condition column "
|
||||
"does not match the default 'control'.\n"
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_accepts_requested_reference_level(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""A configured reference level is accepted when present."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_valid_reference.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition,batch,site\n"
|
||||
"test_name1,test_sample,baseline,b1,s1\n"
|
||||
"test_name2,positive_control,baseline,b1,s2\n"
|
||||
"test_name3,test_sample,treated,b2,s1\n"
|
||||
"test_name4,negative_control,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
"reference_level": "baseline",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out == ""
|
||||
|
||||
|
||||
def test_check_sample_sheet_rejects_missing_requested_reference_level(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""Configured reference levels must exist in the condition column."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_invalid_reference.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"sample_name,type,condition,batch,site\n"
|
||||
"test_name1,test_sample,baseline,b1,s1\n"
|
||||
"test_name2,positive_control,baseline,b1,s2\n"
|
||||
"test_name3,test_sample,treated,b2,s1\n"
|
||||
"test_name4,negative_control,treated,b2,s2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": True,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch,site",
|
||||
"reference_level": "control",
|
||||
})
|
||||
)
|
||||
|
||||
out = _run_check_sample_sheet(sample_sheet_path, params_json, capsys)
|
||||
|
||||
assert out.startswith((
|
||||
"The requested reference level 'control' is not present in "
|
||||
"the condition column.")
|
||||
)
|
||||
|
||||
|
||||
def test_check_sample_sheet_skips_de_checks_when_de_analysis_is_disabled(
|
||||
tmp_path, capsys
|
||||
):
|
||||
"""DE design columns are optional unless DE analysis is enabled."""
|
||||
sample_sheet_path = tmp_path / "sample_sheet_no_condition.csv"
|
||||
sample_sheet_path.write_text(
|
||||
"barcode,alias\n"
|
||||
"barcode01,test_name1\n"
|
||||
"barcode02,test_name2\n"
|
||||
)
|
||||
|
||||
params_json = tmp_path / "params.json"
|
||||
params_json.write_text(
|
||||
json.dumps({
|
||||
"de_analysis": False,
|
||||
"condition_column": "condition",
|
||||
"covariates": "batch",
|
||||
})
|
||||
)
|
||||
|
||||
args = [str(sample_sheet_path), str(params_json)]
|
||||
parsed_args = check_sample_sheet.argparser().parse_args(args)
|
||||
|
||||
try:
|
||||
check_sample_sheet.main(parsed_args)
|
||||
except SystemExit:
|
||||
pass
|
||||
|
||||
out, _ = capsys.readouterr()
|
||||
|
||||
assert out == ""
|
||||
231
bin/workflow_glue/wfg_helpers/validators/wf.py
Normal file
231
bin/workflow_glue/wfg_helpers/validators/wf.py
Normal file
@ -0,0 +1,231 @@
|
||||
"""Workflow-specific sample sheet validators."""
|
||||
|
||||
from collections import Counter
|
||||
import re
|
||||
|
||||
from .default import SampleSheetValidator # noqa: ABS101
|
||||
|
||||
_R_FORMULA_NAME_RE = re.compile(r"^[A-Za-z0-9][A-Za-z0-9._-]*$")
|
||||
|
||||
|
||||
def _split_covariates(value):
|
||||
"""Normalise workflow covariates into a clean list."""
|
||||
if isinstance(value, str):
|
||||
return [item.strip() for item in value.split(",") if item.strip()]
|
||||
|
||||
|
||||
def _validate_r_formula_names(names, label="Column"):
|
||||
"""Validate names against the shared design-name pattern."""
|
||||
empty = names.count("")
|
||||
invalid = [
|
||||
name for name in names
|
||||
if name != "" and (
|
||||
not isinstance(name, str) or _R_FORMULA_NAME_RE.match(name) is None
|
||||
)
|
||||
]
|
||||
if empty or invalid:
|
||||
details = []
|
||||
if empty:
|
||||
details.append('Empty value: ""')
|
||||
if invalid:
|
||||
details.append(f"Invalid names: {', '.join(invalid)}")
|
||||
raise ValueError(
|
||||
f"{label} names must be safe for R formulas. {'; '.join(details)}. "
|
||||
"Names must start with a letter or number and contain "
|
||||
"only letters, numbers, underscores, dots, and hyphens."
|
||||
)
|
||||
|
||||
|
||||
class Covariates(SampleSheetValidator):
|
||||
"""Validate optional DE/DTU covariate columns from workflow params."""
|
||||
|
||||
def __init__(self, wf_params, options=None):
|
||||
"""Initialize with workflow parameters."""
|
||||
super().__init__(wf_params, options)
|
||||
if wf_params.get("covariates"):
|
||||
self.covariates = _split_covariates(wf_params.get("covariates"))
|
||||
else:
|
||||
self.covariates = []
|
||||
|
||||
def on_header(self, header):
|
||||
"""Require configured covariate columns when they are requested."""
|
||||
if not self.wf_params.get("de_analysis"):
|
||||
return
|
||||
# Check values of condition are safe for R
|
||||
try:
|
||||
_validate_r_formula_names(
|
||||
self.covariates,
|
||||
label="Covariate column",
|
||||
)
|
||||
except ValueError as exc:
|
||||
self.log_error(str(exc))
|
||||
|
||||
missing_covariates = [
|
||||
covariate for covariate in self.covariates
|
||||
if covariate not in header
|
||||
]
|
||||
if missing_covariates:
|
||||
self.log_error(
|
||||
f"Missing covariate columns: {', '.join(missing_covariates)}"
|
||||
)
|
||||
|
||||
def add_sheet_row(self, row, lineno):
|
||||
"""Require values in requested design columns for each row."""
|
||||
if not self.wf_params.get("de_analysis"):
|
||||
return
|
||||
|
||||
for covariate in self.covariates:
|
||||
if covariate in row and not row.get(covariate):
|
||||
self.log_error(
|
||||
"Covariate column must not contain missing or empty values",
|
||||
column=covariate,
|
||||
lineno=lineno,
|
||||
)
|
||||
continue
|
||||
|
||||
if covariate in row:
|
||||
try:
|
||||
_validate_r_formula_names(
|
||||
[row.get(covariate)],
|
||||
label="Covariate value",
|
||||
)
|
||||
except ValueError as exc:
|
||||
self.log_error(
|
||||
str(exc),
|
||||
column=covariate,
|
||||
lineno=lineno,
|
||||
)
|
||||
|
||||
|
||||
class ConditionReplicates(SampleSheetValidator):
|
||||
"""Validate the condition column and check that each level has replicates."""
|
||||
|
||||
def __init__(self, wf_params, options=None):
|
||||
"""Initialize with workflow parameters."""
|
||||
super().__init__(wf_params, options)
|
||||
self.condition_column = wf_params.get("condition_column")
|
||||
self.has_condition = False
|
||||
self.condition_counts = Counter()
|
||||
|
||||
def on_header(self, header):
|
||||
"""Validate and track whether the sample sheet contains a condition column."""
|
||||
if not self.wf_params.get("de_analysis"):
|
||||
return
|
||||
|
||||
try:
|
||||
_validate_r_formula_names(
|
||||
[self.condition_column],
|
||||
label="Design column",
|
||||
)
|
||||
except ValueError as exc:
|
||||
self.log_error(str(exc))
|
||||
|
||||
self.has_condition = (
|
||||
self.condition_column is not None and self.condition_column in header
|
||||
)
|
||||
|
||||
if self.condition_column and self.condition_column not in header:
|
||||
self.log_error(
|
||||
f"Sample sheet must contain the '{self.condition_column}' column.",
|
||||
column=self.condition_column,
|
||||
)
|
||||
|
||||
def add_sheet_row(self, row, lineno):
|
||||
"""Validate condition values and count samples for each condition."""
|
||||
if not self.has_condition:
|
||||
return
|
||||
|
||||
condition = row.get(self.condition_column)
|
||||
if not condition:
|
||||
self.log_error(
|
||||
"Condition column must not contain missing or empty values",
|
||||
column=self.condition_column,
|
||||
lineno=lineno,
|
||||
)
|
||||
return
|
||||
# Check values of condition are safe for R
|
||||
try:
|
||||
_validate_r_formula_names(
|
||||
[condition],
|
||||
label="Condition value",
|
||||
)
|
||||
except ValueError as exc:
|
||||
self.log_error(str(exc), column=self.condition_column, lineno=lineno)
|
||||
|
||||
self.condition_counts[condition] += 1
|
||||
|
||||
@property
|
||||
def is_valid(self):
|
||||
"""Check condition levels and replicates are sufficient for DE."""
|
||||
valid = True
|
||||
if self.has_condition and len(self.condition_counts) < 2:
|
||||
self.log_error(
|
||||
"Condition column must contain at least 2 condition levels",
|
||||
column=self.condition_column,
|
||||
)
|
||||
valid = False
|
||||
for condition, count in self.condition_counts.items():
|
||||
if count < 2:
|
||||
self.log_error(
|
||||
f"Condition must have at least 2 samples: {condition}",
|
||||
column=self.condition_column,
|
||||
)
|
||||
valid = False
|
||||
return valid and super().is_valid
|
||||
|
||||
|
||||
class ReferenceLevel(SampleSheetValidator):
|
||||
"""Validate the DE reference level against observed condition values."""
|
||||
|
||||
def __init__(self, wf_params, options=None):
|
||||
"""Initialize with workflow parameters."""
|
||||
super().__init__(wf_params, options)
|
||||
self.condition_column = wf_params.get("condition_column")
|
||||
self.has_condition = False
|
||||
self.condition_values = set()
|
||||
|
||||
def on_header(self, header):
|
||||
"""Track whether reference-level validation should run."""
|
||||
self.has_condition = (
|
||||
self.wf_params.get("de_analysis")
|
||||
and self.condition_column is not None
|
||||
and self.condition_column in header
|
||||
)
|
||||
|
||||
def add_sheet_row(self, row, lineno):
|
||||
"""Collect condition values for reference-level validation."""
|
||||
if not self.has_condition:
|
||||
return
|
||||
|
||||
condition = row.get(self.condition_column)
|
||||
if not condition:
|
||||
return
|
||||
|
||||
self.condition_values.add(condition)
|
||||
|
||||
@property
|
||||
def is_valid(self):
|
||||
"""Validate the configured or inferred reference level."""
|
||||
if not self.has_condition:
|
||||
return super().is_valid
|
||||
|
||||
reference_level = self.wf_params.get("reference_level")
|
||||
if reference_level is None:
|
||||
if "control" in self.condition_values:
|
||||
reference_level = "control"
|
||||
else:
|
||||
self.log_error(
|
||||
(
|
||||
"Provide --reference_level when the condition column "
|
||||
"does not match the default 'control'."
|
||||
)
|
||||
)
|
||||
return False
|
||||
|
||||
if reference_level not in self.condition_values:
|
||||
self.log_error((
|
||||
f"The requested reference level '{reference_level}' is not present "
|
||||
"in the condition column."))
|
||||
return False
|
||||
|
||||
return super().is_valid
|
||||
@ -160,35 +160,10 @@ bambu_resolve_chunk_dirs <- function(args) {
|
||||
chunk_dirs
|
||||
}
|
||||
|
||||
bambu_read_sample_sheet <- function(path) {
|
||||
header <- names(utils::read.csv(path, nrows = 0, check.names = FALSE))
|
||||
char_cols <- intersect(c("alias", "sample_id"), header)
|
||||
col_classes <- stats::setNames(rep("character", length(char_cols)), char_cols)
|
||||
utils::read.csv(
|
||||
path,
|
||||
check.names = FALSE,
|
||||
stringsAsFactors = FALSE,
|
||||
colClasses = col_classes
|
||||
)
|
||||
}
|
||||
|
||||
bambu_resolve_inputs <- function(args, bamfile_list_ctor = Rsamtools::BamFileList) {
|
||||
sample_df <- NULL
|
||||
if (!bambu_missing(args$sample_sheet)) {
|
||||
sample_df <- bambu_read_sample_sheet(args$sample_sheet)
|
||||
if (!"alias" %in% names(sample_df)) {
|
||||
stop("Sample sheet must contain an 'alias' column.", call. = FALSE)
|
||||
}
|
||||
duplicate_sample_aliases <- unique(sample_df$alias[duplicated(sample_df$alias)])
|
||||
if (length(duplicate_sample_aliases) > 0) {
|
||||
stop(
|
||||
sprintf(
|
||||
"Sample sheet aliases must be unique; duplicated aliases: %s",
|
||||
paste(duplicate_sample_aliases, collapse = ", ")
|
||||
),
|
||||
call. = FALSE
|
||||
)
|
||||
}
|
||||
sample_df <- workflow_glue_r_read_sample_sheet(args$sample_sheet)
|
||||
}
|
||||
|
||||
bam_paths <- workflow_glue_r_parse_csv_list(args$bams)
|
||||
@ -1052,7 +1027,7 @@ bambu_collate_chunk_outputs <- function(
|
||||
})
|
||||
raw_se <- bambu_combine_transcript_chunks(tx_ses)
|
||||
|
||||
sample_df <- bambu_read_sample_sheet(file.path(chunk_dirs[[1]], "samples.csv"))
|
||||
sample_df <- workflow_glue_r_read_sample_sheet(file.path(chunk_dirs[[1]], "samples.csv"))
|
||||
|
||||
gene_se <- gene_expression_fn(raw_se)
|
||||
filtered <- bambu_filter_transcripts(raw_se)
|
||||
|
||||
@ -129,3 +129,15 @@ workflow_glue_r_annotation_name_maps <- function(annotation_path) {
|
||||
)
|
||||
)
|
||||
}
|
||||
|
||||
workflow_glue_r_read_sample_sheet <- function(path) {
|
||||
header <- names(utils::read.csv(path, nrows = 0, check.names = FALSE))
|
||||
char_cols <- intersect(c("alias", "sample_id"), header)
|
||||
col_classes <- stats::setNames(rep("character", length(char_cols)), char_cols)
|
||||
utils::read.csv(
|
||||
path,
|
||||
check.names = FALSE,
|
||||
stringsAsFactors = FALSE,
|
||||
colClasses = col_classes
|
||||
)
|
||||
}
|
||||
@ -64,37 +64,6 @@ de_validate_inputs <- function(tx_se, gene_se, sample_df, argv) {
|
||||
label = "Design column"
|
||||
)
|
||||
|
||||
if (!"alias" %in% names(sample_df)) {
|
||||
stop("Sample sheet must contain an 'alias' column.", call. = FALSE)
|
||||
}
|
||||
duplicate_sample_aliases <- unique(sample_df$alias[duplicated(sample_df$alias)])
|
||||
if (length(duplicate_sample_aliases) > 0) {
|
||||
stop(
|
||||
sprintf(
|
||||
"Sample sheet aliases must be unique; duplicated aliases: %s",
|
||||
paste(duplicate_sample_aliases, collapse = ", ")
|
||||
),
|
||||
call. = FALSE
|
||||
)
|
||||
}
|
||||
if (!(argv$condition_column %in% names(sample_df))) {
|
||||
stop(
|
||||
sprintf("Sample sheet must contain the '%s' column.", argv$condition_column),
|
||||
call. = FALSE
|
||||
)
|
||||
}
|
||||
|
||||
missing_covariates <- setdiff(covariates, names(sample_df))
|
||||
if (length(missing_covariates) > 0) {
|
||||
stop(
|
||||
sprintf(
|
||||
"Missing covariate columns: %s",
|
||||
paste(missing_covariates, collapse = ", ")
|
||||
),
|
||||
call. = FALSE
|
||||
)
|
||||
}
|
||||
|
||||
if (any(duplicated(colnames(tx_se)))) {
|
||||
stop("Transcript RDS sample names must be unique.", call. = FALSE)
|
||||
}
|
||||
@ -145,17 +114,7 @@ de_validate_inputs <- function(tx_se, gene_se, sample_df, argv) {
|
||||
|
||||
reference_level <- argv$reference_level
|
||||
if (is.null(reference_level)) {
|
||||
if ("control" %in% condition_values) {
|
||||
reference_level <- "control"
|
||||
} else {
|
||||
stop(
|
||||
"Provide --reference_level when the condition column does not contain 'control'.",
|
||||
call. = FALSE
|
||||
)
|
||||
}
|
||||
}
|
||||
if (!(reference_level %in% condition_values)) {
|
||||
stop("The requested reference level is not present in the condition column.", call. = FALSE)
|
||||
}
|
||||
|
||||
sample_df[[argv$condition_column]] <- factor(sample_df[[argv$condition_column]])
|
||||
@ -788,11 +747,7 @@ main_run_de_analysis <- function(args) {
|
||||
|
||||
tx_se <- readRDS(args$transcript_rds)
|
||||
gene_se <- readRDS(args$gene_rds)
|
||||
sample_df <- utils::read.csv(
|
||||
args$sample_sheet,
|
||||
check.names = FALSE,
|
||||
stringsAsFactors = FALSE
|
||||
)
|
||||
sample_df <- workflow_glue_r_read_sample_sheet(args$sample_sheet)
|
||||
validated <- de_validate_inputs(tx_se, gene_se, sample_df, args)
|
||||
sample_df <- validated$sample_df
|
||||
covariates <- validated$covariates
|
||||
|
||||
@ -135,41 +135,6 @@ testthat::test_that("unique sample aliases required", {
|
||||
bambu_resolve_inputs(args, bamfile_list_ctor = function(paths, yieldSize) paths),
|
||||
"Provide one alias per BAM in --bams"
|
||||
)
|
||||
|
||||
missing_alias_sheet <- tempfile(fileext = ".csv")
|
||||
writeLines(
|
||||
paste(
|
||||
"condition",
|
||||
"control",
|
||||
sep = "\n"
|
||||
),
|
||||
missing_alias_sheet
|
||||
)
|
||||
args <- list(
|
||||
bams = "sampleA.bam",
|
||||
aliases = "sampleA",
|
||||
sample_sheet = missing_alias_sheet
|
||||
)
|
||||
testthat::expect_error(
|
||||
bambu_resolve_inputs(args, bamfile_list_ctor = function(paths, yieldSize) paths),
|
||||
"Sample sheet must contain an 'alias' column"
|
||||
)
|
||||
|
||||
duplicate_alias_sheet <- tempfile(fileext = ".csv")
|
||||
writeLines(
|
||||
paste(
|
||||
"alias,condition",
|
||||
"sampleA,control",
|
||||
"sampleA,treated",
|
||||
sep = "\n"
|
||||
),
|
||||
duplicate_alias_sheet
|
||||
)
|
||||
args$sample_sheet <- duplicate_alias_sheet
|
||||
testthat::expect_error(
|
||||
bambu_resolve_inputs(args, bamfile_list_ctor = function(paths, yieldSize) paths),
|
||||
"Sample sheet aliases must be unique"
|
||||
)
|
||||
})
|
||||
|
||||
# Sample sheet rows must align with BAM file order.
|
||||
|
||||
@ -13,53 +13,6 @@ testthat::test_that("covariates parsed and trimmed", {
|
||||
)
|
||||
})
|
||||
|
||||
# Sample sheet must have 'alias' column matching SE colnames, condition column, and all covariates.
|
||||
# Aliases must be unique. Missing columns should fail fast before passing to DESeq2/DRIMSeq.
|
||||
testthat::test_that("sample sheet structure validated", {
|
||||
tx_se <- make_test_tx_se()
|
||||
gene_se <- make_test_gene_se()
|
||||
argv <- list(
|
||||
transcript_rds = "transcripts.rds",
|
||||
gene_rds = "genes.rds",
|
||||
sample_sheet = "sample_sheet.csv",
|
||||
condition_column = "condition",
|
||||
covariates = "batch",
|
||||
reference_level = NULL
|
||||
)
|
||||
argv <- workflow_glue_r_normalise_args(argv, de_analysis_arg_spec())
|
||||
|
||||
missing_alias <- data.frame(condition = rep(c("control", "treated"), each = 3))
|
||||
testthat::expect_error(
|
||||
de_validate_inputs(tx_se, gene_se, missing_alias, argv),
|
||||
"Sample sheet must contain an 'alias' column"
|
||||
)
|
||||
|
||||
sample_df <- data.frame(
|
||||
alias = colnames(tx_se),
|
||||
batch = rep(c("b1", "b2", "b1"), 2),
|
||||
stringsAsFactors = FALSE
|
||||
)
|
||||
testthat::expect_error(
|
||||
de_validate_inputs(tx_se, gene_se, sample_df, argv),
|
||||
"Sample sheet must contain the 'condition' column"
|
||||
)
|
||||
|
||||
sample_df$condition <- rep(c("control", "treated"), each = 3)
|
||||
argv$covariates <- "batch,site"
|
||||
testthat::expect_error(
|
||||
de_validate_inputs(tx_se, gene_se, sample_df, argv),
|
||||
"Missing covariate columns: site"
|
||||
)
|
||||
|
||||
duplicate_aliases <- sample_df
|
||||
duplicate_aliases$alias[2] <- duplicate_aliases$alias[1]
|
||||
argv$covariates <- "batch"
|
||||
testthat::expect_error(
|
||||
de_validate_inputs(tx_se, gene_se, duplicate_aliases, argv),
|
||||
"Sample sheet aliases must be unique"
|
||||
)
|
||||
})
|
||||
|
||||
# R formulas break on spaces/hyphens in column names (e.g., ~ `time point` produces errors).
|
||||
# Validate condition_column and covariate names are safe (alphanumeric + underscore).
|
||||
testthat::test_that("formula-unsafe column names rejected", {
|
||||
@ -122,16 +75,16 @@ testthat::test_that("DTU transcript output renames contrast-specific log2fold co
|
||||
)
|
||||
})
|
||||
|
||||
# Sample aliases CAN have spaces/hyphens (they're not used in formulas, just for matching).
|
||||
# Sample aliases CAN have hyphens (they're not used in formulas, just for matching).
|
||||
# Sample sheet rows can be in different order than SE columns - should reorder automatically.
|
||||
testthat::test_that("non-syntactic aliases allowed, sheets reordered", {
|
||||
sample_names <- c(
|
||||
"1control",
|
||||
"control-2",
|
||||
"control rep 3",
|
||||
"4treated",
|
||||
"control _rep 3",
|
||||
"04",
|
||||
"treated-5",
|
||||
"treated rep 6"
|
||||
"treated-rep.6"
|
||||
)
|
||||
tx_se <- make_test_tx_se(sample_names = sample_names)
|
||||
gene_se <- make_test_gene_se(sample_names = sample_names)
|
||||
@ -195,48 +148,6 @@ testthat::test_that("reference level defaults to control", {
|
||||
)
|
||||
})
|
||||
|
||||
# If no "control" level exists, user MUST provide --reference_level explicitly.
|
||||
# Specified reference_level must exist in the condition column values.
|
||||
testthat::test_that("explicit reference level required without control", {
|
||||
tx_se <- make_test_tx_se(
|
||||
sample_names = c(
|
||||
"baseline_rep1", "baseline_rep2", "baseline_rep3",
|
||||
"treated_rep1", "treated_rep2", "treated_rep3"
|
||||
)
|
||||
)
|
||||
gene_se <- make_test_gene_se(
|
||||
sample_names = c(
|
||||
"baseline_rep1", "baseline_rep2", "baseline_rep3",
|
||||
"treated_rep1", "treated_rep2", "treated_rep3"
|
||||
)
|
||||
)
|
||||
sample_df <- data.frame(
|
||||
alias = colnames(tx_se),
|
||||
condition = rep(c("baseline", "treated"), each = 3),
|
||||
batch = rep(c("b1", "b2", "b1"), 2),
|
||||
stringsAsFactors = FALSE
|
||||
)
|
||||
argv <- list(
|
||||
transcript_rds = "transcripts.rds",
|
||||
gene_rds = "genes.rds",
|
||||
sample_sheet = "sample_sheet.csv",
|
||||
condition_column = "condition",
|
||||
covariates = "batch",
|
||||
reference_level = NULL
|
||||
)
|
||||
argv <- workflow_glue_r_normalise_args(argv, de_analysis_arg_spec())
|
||||
|
||||
testthat::expect_error(
|
||||
de_validate_inputs(tx_se, gene_se, sample_df, argv),
|
||||
"Provide --reference_level"
|
||||
)
|
||||
|
||||
argv$reference_level <- "does_not_exist"
|
||||
testthat::expect_error(
|
||||
de_validate_inputs(tx_se, gene_se, sample_df, argv),
|
||||
"requested reference level is not present"
|
||||
)
|
||||
})
|
||||
|
||||
# Count matrices must be numeric, non-NA, non-zero totals per sample.
|
||||
# Transcript and gene SE sample names must match exactly (same order, same values).
|
||||
|
||||
18
main.nf
18
main.nf
@ -236,6 +236,24 @@ workflow {
|
||||
"force_alignment": params.force_alignment,
|
||||
] + ingress_args, ref_genome)
|
||||
}
|
||||
|
||||
|
||||
sample_sheet_aliases = sample_sheet == OPTIONAL_FILE ?
|
||||
null :
|
||||
sample_sheet
|
||||
.splitCsv(header: true, quote: '"')
|
||||
.collect { it.alias }
|
||||
.findAll { it != null }
|
||||
.toSet()
|
||||
samples.subscribe { meta, xam, xai, stats ->
|
||||
if (sample_sheet_aliases != null && !sample_sheet_aliases.contains(meta.alias)) {
|
||||
throw new Exception(
|
||||
"Sample alias '${meta.alias}' was not found in the sample_sheet alias column."
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
analysis_samples = samples
|
||||
.filter { meta, xam, xai, stats ->
|
||||
boolean is_excluded = false
|
||||
|
||||
@ -1,28 +1,6 @@
|
||||
nextflow.enable.dsl = 2
|
||||
|
||||
|
||||
process checkExperimentDesign {
|
||||
label "wf_common"
|
||||
cpus 1
|
||||
memory "2 GB"
|
||||
input:
|
||||
path sample_sheet
|
||||
output:
|
||||
path "validated.ok", emit: ok
|
||||
script:
|
||||
String covariates_arg = params.covariates ? "--covariates '${params.covariates}'" : ""
|
||||
String reference_arg = params.reference_level ? "--reference_level '${params.reference_level}'" : ""
|
||||
"""
|
||||
workflow-glue check_experiment_design \
|
||||
--sample_sheet "${sample_sheet}" \
|
||||
--condition_column "${params.condition_column}" \
|
||||
${covariates_arg} \
|
||||
${reference_arg}
|
||||
touch validated.ok
|
||||
"""
|
||||
}
|
||||
|
||||
|
||||
process runDifferentialAnalysis {
|
||||
label "wf_transcriptomes"
|
||||
cpus { params.threads ?: 4 }
|
||||
@ -31,7 +9,6 @@ process runDifferentialAnalysis {
|
||||
path transcript_rds
|
||||
path gene_rds
|
||||
path sample_sheet
|
||||
path validation_token
|
||||
output:
|
||||
path "de_analysis", emit: dir
|
||||
script:
|
||||
@ -56,8 +33,7 @@ workflow differential_expression {
|
||||
gene_rds
|
||||
sample_sheet
|
||||
main:
|
||||
validated = checkExperimentDesign(sample_sheet)
|
||||
results = runDifferentialAnalysis(transcript_rds, gene_rds, sample_sheet, validated.ok)
|
||||
results = runDifferentialAnalysis(transcript_rds, gene_rds, sample_sheet)
|
||||
emit:
|
||||
dir = results.dir
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user