302 lines
11 KiB
Python
302 lines
11 KiB
Python
from pathlib import Path
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import subprocess
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import sys
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import pytest
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import yaml
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ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from apps.cli.run_rnaseq_de import build_de_plan, generate_modular_r_script, run_deseq2
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from apps.cli.run_rnaseq_fgsea import find_de_results
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from apps.cli.run_samples_autofill import design_from_samples
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from gfa_core.rnaseq_de_design import (
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build_de_design_review,
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plan_rnaseq_de_design,
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)
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def _factorial(*, drop=(), time_values=None):
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samples = {}
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for genotype in ("G1", "G2"):
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for condition, role in (("Control", "control"), ("Salt", "compare")):
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for replicate in (1, 2):
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sample = f"{genotype}_{condition}_{replicate}"
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if sample in drop:
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continue
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row = {
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"condition": condition,
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"genotype": genotype,
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"group_role": role,
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"replicate": replicate,
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"include": True,
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}
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if time_values:
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row["time"] = time_values[replicate - 1]
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samples[sample] = row
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return samples
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def _plan(samples, module=""):
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matrix_samples = list(samples)
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groups = {sample: row["condition"] for sample, row in samples.items()}
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return build_de_plan({"samples": samples, "de": {"strategy": "auto"}}, matrix_samples, groups, user_module=module)
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def test_complete_factorial_selects_m4_and_keeps_m3_simple_effects():
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plan = _plan(_factorial())
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assert plan["module"] == "M4"
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assert plan["advanced_factor"] == "genotype"
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assert plan["comparisons"] == [
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["G1__Salt", "G1__Control"],
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["G2__Salt", "G2__Control"],
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["G2__Control", "G1__Control"],
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["G2__Salt", "G1__Salt"],
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]
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assert plan["comparison_axis"] == "condition"
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assert plan["reference_condition"] == "Control"
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assert plan["reference_factor"] == "G1"
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assert plan["interaction_full"] == "~ genotype * condition"
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assert plan["fallback_from"] == ""
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def test_incomplete_factorial_degrades_to_valid_m3_strata():
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samples = _factorial(drop={"G2_Salt_1", "G2_Salt_2"})
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plan = _plan(samples)
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assert plan["module"] == "M3"
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assert plan["comparisons"] == [["G1__Salt", "G1__Control"]]
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assert plan["fallback_from"] == "M4"
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assert plan["skipped_comparisons"]
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def test_varying_time_is_not_silently_ignored_by_m3_m4():
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with pytest.raises(ValueError, match="time"):
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_plan(_factorial(time_values=("0h", "6h")))
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def test_m4_script_emits_group_contrasts_and_unsigned_lrt(tmp_path):
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samples = _factorial()
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plan = _plan(samples)
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script = generate_modular_r_script(
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tmp_path / "counts.txt",
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list(samples),
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plan,
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tmp_path,
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0.05,
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1.0,
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)
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assert "dds_group" in script
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assert 'test="LRT"' in script
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assert "reduced=~ genotype + condition" in script
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assert "genotype_by_condition.interaction_LRT.DE_results.txt" in script
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assert "dds_wald" in script
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assert "interaction_Wald" in script
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assert "falling back to ~condition" not in script
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def test_group_role_may_define_genotype_axis_in_standard_factorial():
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samples = {}
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for genotype, role in (("WT", "control"), ("ire1dm", "compare")):
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for condition in ("DMSO", "Tm"):
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for replicate in (1, 2):
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sample = f"{genotype}_{condition}_{replicate}"
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samples[sample] = {
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"genotype": genotype,
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"condition": condition,
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"group_role": role,
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"replicate": replicate,
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"include": True,
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}
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plan = _plan(samples)
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assert plan["module"] == "M4"
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assert plan["comparison_axis"] == "genotype"
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assert plan["stratify_axis"] == "condition"
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assert plan["reference_factor"] == "WT"
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assert plan["reference_condition"] == "DMSO"
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assert plan["comparisons"] == [
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["ire1dm__DMSO", "WT__DMSO"],
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["ire1dm__Tm", "WT__Tm"],
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["WT__Tm", "WT__DMSO"],
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["ire1dm__Tm", "ire1dm__DMSO"],
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]
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def test_blank_roles_use_common_reference_names_without_rejecting_m4():
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samples = {}
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for genotype in ("WT", "ire1dm"):
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for condition in ("DMSO", "Tm"):
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for replicate in (1, 2):
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sample = f"{genotype}_{condition}_{replicate}"
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samples[sample] = {
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"genotype": genotype,
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"condition": condition,
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"group_role": "",
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"replicate": replicate,
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"include": True,
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}
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plan = _plan(samples)
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assert plan["module"] == "M4"
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assert plan["reference_factor"] == "WT"
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assert plan["reference_condition"] == "DMSO"
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assert plan["factor_reference_source"] == "semantic"
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assert plan["condition_reference_source"] == "semantic"
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def test_fgsea_excludes_unsigned_m4_lrt(tmp_path):
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directional = tmp_path / "Os.rnaseq_de.G1__Salt_vs_G1__Control.DE_results.txt"
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interaction = tmp_path / "Os.rnaseq_de.genotype_by_condition.interaction_LRT.DE_results.txt"
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directional.write_text("gene_id\tstat\n", encoding="utf-8")
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interaction.write_text("gene_id\tstat\n", encoding="utf-8")
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assert find_de_results(tmp_path, "Os") == [directional]
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with pytest.raises(ValueError, match="not eligible"):
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find_de_results(tmp_path, "Os", "genotype_by_condition.interaction_LRT")
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def test_frontend_review_matches_executable_m4_plan():
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samples = {}
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for genotype, role in (("WT", "control"), ("ire1dm", "compare")):
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for condition in ("DMSO", "Tm"):
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for replicate in (1, 2):
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sample = f"{genotype}_{condition}_{replicate}"
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samples[sample] = {
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"genotype": genotype,
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"condition": condition,
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"group_role": role,
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"replicate": replicate,
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"include": True,
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}
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plan = plan_rnaseq_de_design(samples, matrix_samples=list(samples))
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review = build_de_design_review(plan)
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assert review["module"] == "M4"
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assert review["comparison_axis"] == "genotype"
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assert [item["display"] for item in review["comparisons"]] == [
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"DMSO 条件下：ire1dm vs WT",
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"Tm 条件下：ire1dm vs WT",
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"WT 中：Tm vs DMSO",
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"ire1dm 中：Tm vs DMSO",
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]
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assert review["interaction"] == {
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"enabled": True,
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"display": "genotype × condition 交互效应",
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"methods": ["LRT", "Wald"],
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}
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def test_saved_module_override_is_used_by_de_execution():
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samples = _factorial()
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groups = {sample: row["condition"] for sample, row in samples.items()}
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plan = build_de_plan(
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{"samples": samples, "de": {"strategy": "auto", "module": "M3"}},
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list(samples),
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groups,
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)
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assert plan["module"] == "M3"
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assert plan["fallback_from"] == "M4"
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def test_optional_batch_is_added_to_m1_and_frontend_review():
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samples = {}
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for condition, role in (("Control", "control"), ("Salt", "compare")):
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for replicate, batch in ((1, "B1"), (2, "B2")):
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sample = f"{condition}_{replicate}"
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samples[sample] = {
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"condition": condition,
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"group_role": role,
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"replicate": replicate,
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"batch": batch,
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"include": True,
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}
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plan = plan_rnaseq_de_design(samples, matrix_samples=list(samples))
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review = build_de_design_review(plan)
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assert plan["module"] == "M1"
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assert plan["batch_requested"] is True
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assert plan["batch_used"] is True
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assert plan["design_formula"] == "~ batch + group"
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assert review["batch"]["used"] is True
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assert review["batch"]["levels"] == ["B1", "B2"]
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def test_incomplete_batch_falls_back_without_blocking_design():
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samples = {
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"Control_1": {"condition": "Control", "group_role": "control", "batch": "B1"},
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"Control_2": {"condition": "Control", "group_role": "control", "batch": ""},
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"Salt_1": {"condition": "Salt", "group_role": "compare", "batch": "B1"},
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"Salt_2": {"condition": "Salt", "group_role": "compare", "batch": ""},
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}
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plan = plan_rnaseq_de_design(samples, matrix_samples=list(samples))
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review = build_de_design_review(plan)
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assert plan["module"] == "M1"
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assert plan["batch_requested"] is True
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assert plan["batch_used"] is False
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assert plan["batch_fallback"] is True
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assert plan["design_formula"] == "~ group"
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assert review["batch"]["fallback"] is True
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def test_optional_batch_is_used_by_m4_script(tmp_path):
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samples = _factorial()
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for sample, row in samples.items():
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row["batch"] = "B1" if sample.endswith("_1") else "B2"
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plan = _plan(samples)
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script = generate_modular_r_script(
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tmp_path / "counts.txt",
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list(samples),
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plan,
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tmp_path,
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0.05,
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1.0,
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)
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assert plan["batch_used"] is True
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assert plan["design_formula"] == "~ batch + genotype * condition"
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assert "batch = factor(batch_vals" in script
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assert "design=~ batch + genotype * condition" in script
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assert "reduced=~ batch + genotype + condition" in script
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def test_batch_runtime_failure_retries_once_without_batch(tmp_path, monkeypatch):
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samples = {}
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for condition, role in (("Control", "control"), ("Salt", "compare")):
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for replicate, batch in ((1, "B1"), (2, "B2")):
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sample = f"{condition}_{replicate}"
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samples[sample] = {
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"condition": condition,
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"group_role": role,
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"replicate": replicate,
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"batch": batch,
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"include": True,
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}
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config = tmp_path / "samples.yaml"
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config.write_text(yaml.safe_dump({"samples": samples}), encoding="utf-8")
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count_matrix = tmp_path / "counts.txt"
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count_matrix.write_text(
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"gene_id\tControl_1\tControl_2\tSalt_1\tSalt_2\n"
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"gene1\t10\t11\t30\t31\n"
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"gene2\t20\t19\t5\t6\n",
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encoding="utf-8",
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)
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output_dir = tmp_path / "de"
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output_dir.mkdir()
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calls = []
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def fake_rscript(*args, **kwargs):
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calls.append(args)
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if len(calls) == 1:
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raise subprocess.CalledProcessError(
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1,
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args[0],
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stderr="model matrix is not full rank",
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)
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return subprocess.CompletedProcess(args[0], 0, "", "")
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monkeypatch.setattr("apps.cli.run_rnaseq_de.subprocess.run", fake_rscript)
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status, plan = run_deseq2(count_matrix, config, output_dir)
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assert len(calls) == 2
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assert all(status.values())
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assert plan["batch_requested"] is True
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assert plan["batch_used"] is False
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assert plan["batch_fallback"] is True
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assert (output_dir / "BATCH_FALLBACK.txt").exists()
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assert "batch +" not in (output_dir / "run_deseq2.R").read_text(encoding="utf-8")
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