def test_cell_assign_em(self):
example_rda = os.path.join(base_dir, "tests/cell_assign_test.RData")
sce = SingleCellExperiment.fromRData(example_rda)
cellassigner = CellAssign()
rho = GeneMarkerMatrix(genes=[
"Gene161", "Gene447", "Gene519", "Gene609", "Gene677", "Gene750",
"Gene754", "Gene860", "Gene929", "Gene979"
],
cells=["Groups1", "Groups2"])
res = cellassigner.run_em(sce, rho)
def test_cell_assign_pkl(self):
import pickle
import collections
tenx = TenxAnalysis("tests/pre_igo")
sce = TenX.read10xCounts(tenx)
handle = open("tests/rho_up.pkl","rb")
rho_matrix = pickle.load(handle)
handle.close()
rho = GeneMarkerMatrix(rho_matrix)
cellassigner = CellAssign()
res = cellassigner.run_em(sce, rho)
def test_cell_assign_em(self):
#example_rda = os.path.join(base_dir, "tests/cell_assign_test.RData")
print("Init CellEM")
sce = "sce_final.rdata"
# sce = SingleCellExperiment.fromRData(example_rda)
cellassigner = CellAssign()
# rho_matrix = dict()
# rho_matrix["Group1"] = ["Gene161", "Gene447", "Gene609", "Gene754", "Gene860", "Gene929", "Gene979"]
# rho_matrix["Group2"] = ["Gene161", "Gene447", "Gene609", "Gene754", "Gene860", "Gene929", "Gene979","Gene101","Gene212","Gene400"]
# rho = GeneMarkerMatrix(rho_matrix)
res = cellassigner.run_em(sce, "cell_assign_fit.rdata", "test")