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")