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import pandas as pd
import pytest
from analysis import compute_correlation, differential_expression
def test_compute_correlation():
"""Test correlation computation."""
data = pd.DataFrame({
"clinical_score": [1, 2, 3, 4, 5],
"protein_expression": [2, 4, 6, 8, 10]
})
corr = compute_correlation(data, "clinical_score", "protein_expression")
assert corr > 0.99, "Correlation should be close to 1 for linear data"
def test_differential_expression():
"""Test differential expression analysis."""
group1 = pd.DataFrame({
"Protein1": [10, 15, 12],
"Protein2": [5, 7, 6]
})
group2 = pd.DataFrame({
"Protein1": [20, 25, 22],
"Protein2": [10, 12, 11]
})
proteins = pd.concat([group1, group2], axis=1)
results = differential_expression(group1, group2, proteins)
assert isinstance(results, pd.DataFrame), "Results should be a DataFrame"
assert "logFC" in results.columns, "Results should include logFC column"
assert "p-value" in results.columns, "Results should include p-value column"
assert results["logFC"].iloc[0] > 0, "logFC should reflect upregulation"
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