feat: diffexp returns two genesets (#2230)

* feat: return two lists for diffexp (#2221)

* sp

* split out derive sort order, tests passing

* sp

* return diff exp results in two lists

* update

* copy implementation over to desktop

* add tests for two lists

* small fixes to complete backend implementation

* accept new diffexp response

* map diff exp response to genesets

* delete )

* name diffexp genesets with population names

* take constants out of state and allow width prop to override

* shorten mini-histo properly truncate and resize depending on expansion

* prepend new genesets

* rename data within diffexp action

* backend

* move diffexp ttest to common code module, update tests

* update for unit tests

* reference actual var

Co-authored-by: Madison Dunitz <madison.dunitz@chanzuckerberg.com>
Co-authored-by: Madison Dunitz <dunitzm@gmail.com>
This commit is contained in:
Severiano Badajoz
2021-06-08 21:02:19 +00:00
committed by GitHub
co-authored by Madison Dunitz Madison Dunitz
parent 7ed53c0f5b
commit 28b526b3fc
25 changed files with 268 additions and 284 deletions
@@ -158,7 +158,8 @@ class EndPoints(object):
self.assertEqual(result.status_code, HTTPStatus.OK)
self.assertEqual(result.headers["Content-Type"], "application/json")
result_data = result.json()
self.assertEqual(len(result_data), 7)
self.assertEqual(len(result_data['positive']), 7)
self.assertEqual(len(result_data['negative']), 7)
def test_diff_exp_indices(self):
endpoint = "diffexp/obs"
@@ -173,7 +174,8 @@ class EndPoints(object):
self.assertEqual(result.status_code, HTTPStatus.OK)
self.assertEqual(result.headers["Content-Type"], "application/json")
result_data = result.json()
self.assertEqual(len(result_data), 10)
self.assertEqual(len(result_data['positive']), 10)
self.assertEqual(len(result_data['negative']), 10)
def test_get_annotations_var_fbs(self):
endpoint = "annotations/var"
@@ -382,6 +384,7 @@ class EndPoints(object):
query_hash = hashlib.sha1(query.encode()).hexdigest()
url = f"{self.URL_BASE}{endpoint}?key={query_hash}"
result = self.session.post(url, headers=headers, data=query)
self.assertEqual(result.status_code, HTTPStatus.OK)
self.assertEqual(result.headers["Content-Type"], "application/octet-stream")
df = decode_fbs.decode_matrix_FBS(result.content)
@@ -4,7 +4,8 @@ import unittest
import numpy as np
from backend.czi_hosted.compute import diffexp_generic, diffexp_cxg
from backend.czi_hosted.compute import diffexp_cxg
from backend.common.compute import diffexp_generic
from backend.czi_hosted.compute.diffexp_cxg import diffexp_ttest
from backend.czi_hosted.converters.h5ad_data_file import H5ADDataFile
from backend.common.fbs.matrix import encode_matrix_fbs, decode_matrix_fbs
@@ -40,21 +41,37 @@ class DiffExpTest(unittest.TestCase):
self.assertTrue(np.isclose(result[2], expect[2], 1e-6, 1e-4))
self.assertTrue(np.isclose(result[3], expect[3], 1e-6, 1e-4))
def check_1_10_2_10(self, results):
"""Checks the results for a specific set of rows selections"""
expects = [
positive_expects = [
[1712, -0.5525154, 0.0051788902660723345, 1.0],
[1575, 1.0317602, 0.007830310753043345, 1.0],
[693, 0.4703904, 0.008715846769131548, 1.0],
[916, 0.9567287, 0.009080596532247588, 1.0],
[77, 0.02665649, 0.010070392939027756, 1.0],
[782, -1.0981874, 0.010161745218916036, 1.0],
[913, 0.5683986, 0.010782030711612685, 1.0],
[910, 0.83164597, 0.014596411069229197, 1.0],
[1727, 0.4127781, 0.015168372104237176, 1.0],
[1443, -0.8241895, 0.015337080567465522, 1.0]
]
negative_expects = [
[956, 0.016060986, 0.0008649321884808977, 1.0],
[1124, 0.96602094, 0.0011717216548271284, 1.0],
[1809, 1.1110606, 0.0019304405196777848, 1.0],
[1712, -0.5525154, 0.0051788902660723345, 1.0],
[1754, 0.5201581, 0.005691734062127954, 1.0],
[948, 1.6390722, 0.006622111055981219, 1.0],
[1810, 0.78618884, 0.007055917428377063, 1.0],
[779, 1.5241305, 0.007202934422407284, 1.0],
[1575, 1.0317602, 0.007830310753043345, 1.0],
[576, 0.97873515, 0.008272092578813124, 1.0],
[538, 0.89114505, 0.01062259019889307, 1.0],
[436, 0.3119122, 0.01127515110543434, 1.0]
]
self.compare_diffexp_results(results, expects)
self.compare_diffexp_results(results['positive'], positive_expects)
self.compare_diffexp_results(results['negative'], negative_expects)
def get_X_col(self, adaptor, cols):
varmask = np.zeros(adaptor.get_shape()[1], dtype=bool)
@@ -80,6 +97,7 @@ class DiffExpTest(unittest.TestCase):
self.check_1_10_2_10(results)
# run it directly
results = diffexp_ttest(adaptor, maskA, maskB, 10)
self.check_1_10_2_10(results)
@@ -128,15 +146,22 @@ class DiffExpTest(unittest.TestCase):
diffexp_results_sparse = diffexp_cxg.diffexp_ttest(adaptor_sparse, maskA, maskB, 10)
diffexp_results_dense = diffexp_cxg.diffexp_ttest(adaptor_dense, maskA, maskB, 10)
self.compare_diffexp_results(diffexp_results_anndata, diffexp_results_sparse)
self.compare_diffexp_results(diffexp_results_anndata, diffexp_results_dense)
self.compare_diffexp_results(diffexp_results_anndata['positive'], diffexp_results_sparse['positive'])
self.compare_diffexp_results(diffexp_results_anndata['negative'], diffexp_results_sparse['negative'])
self.compare_diffexp_results(diffexp_results_anndata['positive'], diffexp_results_dense['positive'])
self.compare_diffexp_results(diffexp_results_anndata['negative'], diffexp_results_dense['negative'])
topcols_pos = np.array([x[0] for x in diffexp_results_anndata['positive']])
topcols_neg = np.array([x[0] for x in diffexp_results_anndata['negative']])
topcols = np.concatenate((topcols_pos, topcols_neg))
topcols = np.array([x[0] for x in diffexp_results_anndata])
cols_anndata = self.get_X_col(adaptor_anndata, topcols)
cols_sparse = self.get_X_col(adaptor_sparse, topcols)
cols_dense = self.get_X_col(adaptor_dense, topcols)
assert cols_anndata.shape[0] == adaptor_sparse.get_shape()[0]
assert cols_anndata.shape[1] == len(diffexp_results_anndata)
assert cols_anndata.shape[1] == len(diffexp_results_anndata['positive']) + len(diffexp_results_anndata['negative'])
def convert(mat, cols):
return decode_matrix_fbs(encode_matrix_fbs(mat, col_idx=cols)).to_numpy()
@@ -152,9 +152,11 @@ class AdaptorTest(unittest.TestCase):
f1 = {"filter": {"obs": {"index": [[0, 500]]}}}
f2 = {"filter": {"obs": {"index": [[500, 1000]]}}}
result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"]))
self.assertEqual(len(result), 10)
self.assertEqual(len(result['positive']), 10)
self.assertEqual(len(result['negative']), 10)
result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"], 20))
self.assertEqual(len(result), 20)
self.assertEqual(len(result['positive']), 20)
self.assertEqual(len(result['negative']), 20)
def test_data_frame(self):
f1 = {"var": {"index": [[0, 10]]}}
@@ -30,10 +30,15 @@ class DataLoadAdaptorTest(unittest.TestCase):
def test_diffexp_topN(self):
f1 = {"filter": {"obs": {"index": [[0, 500]]}}}
f2 = {"filter": {"obs": {"index": [[500, 1000]]}}}
result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"]))
self.assertEqual(len(result), 10)
self.assertEqual(len(result['positive']), 10)
self.assertEqual(len(result['negative']), 10)
result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"], 20))
self.assertEqual(len(result), 20)
self.assertEqual(len(result['positive']), 20)
self.assertEqual(len(result['negative']), 20)
class DataLocatorAdaptorTest(unittest.TestCase):