import unittest
import numpy as np
import pandas as pd
from inmoose.edgepy import DGEList, binomTest, exactTest, exactTestBetaApprox, topTags
from inmoose.utils import rnbinom
class Test(unittest.TestCase):
def setUp(self):
y = np.array(rnbinom(80, size=5, mu=20, seed=42)).reshape((20, 4))
y = np.vstack(([0, 0, 0, 0], [0, 0, 2, 2], y))
self.group = np.array([1, 2, 2, 2])
self.d = DGEList(counts=y, group=self.group)
self.d = self.d.estimateGLMCommonDisp()
def test_exactTest_doubletail(self):
e = exactTest(self.d, rejection_region="doubletail")
table_ref = pd.DataFrame(
{
"log2FoldChange": [
0.00000000,
3.51533881,
-0.63058208,
0.41122894,
0.43984489,
0.37139369,
0.13977308,
1.95460401,
-0.01979911,
2.17873153,
-1.01346677,
0.37844670,
-0.93741820,
-0.68416066,
-0.41992156,
0.60973257,
-0.22824454,
1.57918440,
-0.77088316,
-0.40296414,
0.11776420,
0.08922781,
],
"lfcSE": [
4.879406,
4.343170,
0.748468,
0.831304,
0.786678,
0.780016,
0.755259,
0.868254,
0.786410,
0.934109,
0.730749,
0.796331,
0.731355,
0.735686,
0.741946,
0.750018,
0.776667,
0.830651,
0.717838,
0.716268,
0.751390,
0.771176,
],
"logCPM": [
12.12019,
12.70317,
15.56153,
15.07428,
15.52507,
15.56517,
15.77696,
15.83033,
15.29041,
15.58364,
15.78337,
15.38442,
15.78799,
15.76965,
15.74505,
16.12701,
15.31314,
15.84442,
16.13715,
16.30238,
15.82620,
15.52722,
],
"pvalue": [
1.00000000,
0.67966025,
0.37574431,
0.77735744,
0.69008766,
0.72780471,
0.99603624,
0.04941292,
1.00000000,
0.02552397,
0.14116664,
0.74391410,
0.16836537,
0.33562846,
0.55601398,
0.52617216,
0.79259676,
0.09778055,
0.25246831,
0.53871925,
0.99845052,
1.00000000,
],
},
index=[f"gene{i}" for i in range(22)],
)
pd.testing.assert_frame_equal(table_ref, e, check_frame_type=False)
@unittest.skip("R returns NAs, need to find meaningful test data")
def test_exactTest_deviance(self):
e = exactTest(self.d, rejection_region="deviance")
table_ref = pd.DataFrame(
{
"logFC": [
0.00000000,
3.51533881,
-0.63058208,
0.41122894,
0.43984489,
0.37139369,
0.13977308,
1.95460401,
-0.01979911,
2.17873153,
-1.01346677,
0.37844670,
-0.93741820,
-0.68416066,
-0.41992156,
0.60973257,
-0.22824454,
1.57918440,
-0.77088316,
-0.40296414,
0.11776420,
0.08922781,
],
"logCPM": [
12.12019,
12.70317,
15.56153,
15.07428,
15.52507,
15.56517,
15.77696,
15.83033,
15.29041,
15.58364,
15.78337,
15.38442,
15.78799,
15.76965,
15.74505,
16.12701,
15.31314,
15.84442,
16.13715,
16.30238,
15.82620,
15.52722,
],
"PValue": [
1.00000,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
np.nan,
],
}
)
self.assertTrue(np.allclose(table_ref["logFC"], e["logFC"], atol=1e-6, rtol=0))
self.assertTrue(
np.allclose(table_ref["logCPM"], e["logCPM"], atol=1e-5, rtol=0)
)
self.assertTrue(
np.allclose(table_ref["PValue"], e["PValue"], atol=1e-6, rtol=0)
)
def test_exactTest_smallp(self):
e = exactTest(self.d, rejection_region="smallp")
table_ref = pd.DataFrame(
{
"log2FoldChange": [
0.00000000,
3.51533881,
-0.63058208,
0.41122894,
0.43984489,
0.37139369,
0.13977308,
1.95460401,
-0.01979911,
2.17873153,
-1.01346677,
0.37844670,
-0.93741820,
-0.68416066,
-0.41992156,
0.60973257,
-0.22824454,
1.57918440,
-0.77088316,
-0.40296414,
0.11776420,
0.08922781,
],
"lfcSE": [
4.879406,
4.343170,
0.748468,
0.831304,
0.786678,
0.780016,
0.755259,
0.868254,
0.786410,
0.934109,
0.730749,
0.796331,
0.731355,
0.735686,
0.741946,
0.750018,
0.776667,
0.830651,
0.717838,
0.716268,
0.751390,
0.771176,
],
"logCPM": [
12.12019,
12.70317,
15.56153,
15.07428,
15.52507,
15.56517,
15.77696,
15.83033,
15.29041,
15.58364,
15.78337,
15.38442,
15.78799,
15.76965,
15.74505,
16.12701,
15.31314,
15.84442,
16.13715,
16.30238,
15.82620,
15.52722,
],
"pvalue": [
1.00000000,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
0.03903554,
],
},
index=[f"gene{i}" for i in range(22)],
)
pd.testing.assert_frame_equal(table_ref, e, check_frame_type=False)
def test_exactTestBetaApprox(self):
pref = [6.988452e-145, 5.981632e-124]
pval = exactTestBetaApprox(
np.array([[1000, 1200], [1300, 1400]]),
np.array([[2000, 2200], [2300, 2400]]),
)
self.assertTrue(np.allclose(pref, pval, atol=1e-6, rtol=0))
def test_binomTest(self):
pval = binomTest(self.d.counts.iloc[:, 0], self.d.counts.iloc[:, 1])
pref = [
1.000000e00,
1.000000e00,
2.275075e-01,
3.385877e-01,
9.734914e-03,
5.510056e-02,
2.413184e-01,
6.708009e-05,
7.109008e-01,
1.204722e-03,
2.277012e-02,
3.097011e-01,
4.480458e-02,
8.989952e-01,
4.168068e-02,
7.667345e-01,
1.000000e00,
8.761834e-07,
3.168496e-03,
2.395773e-01,
6.406607e-01,
1.000000e00,
]
self.assertTrue(np.allclose(pval, pref, atol=1e-6, rtol=0))
def test_topTags(self):
t = topTags(exactTest(self.d))
self.assertTrue(
np.array_equal(
t.table.index,
[
"gene9",
"gene7",
"gene17",
"gene10",
"gene12",
"gene18",
"gene13",
"gene2",
"gene15",
"gene19",
],
)
)
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