sccoda
We advise to import scCODA in a python session via:
import sccoda
dat = sccoda.util.cell_composition_data
ana = sccoda.util.compositional_analysis
viz = sccoda.util.data_visualizationThe workflow in scCODA starts with reading in cell count data (dat) and visualizing them (viz) or synthetically generating cell count data (util.data_generation).
Integrating data sources (dat) (scanpy or pandas)
sccoda.util.cell_composition_data.from_pandas sccoda.util.cell_composition_data.from_scanpy sccoda.util.cell_composition_data.from_scanpy_dir sccoda.util.cell_composition_data.from_scanpy_list sccoda.util.cell_composition_data.read_anndata_one_sample
Synthetic data generation
sccoda.util.data_generation.generate_case_control sccoda.util.data_generation.b_w_from_abs_change sccoda.util.data_generation.counts_from_first sccoda.util.data_generation.sparse_effect_matrix
Compositional data visualization
Compositional datasets can be plotted via the methods in util.data_visualization.
sccoda.util.data_visualization.stacked_barplot sccoda.util.data_visualization.boxplots sccoda.util.data_visualization.stackbar
Using the scCODA model is easiest by generating an instance of ana.CompositionalAnalysis. By specifying the formula via the patsy syntax, many combinations and transformations of the covariates can be performed without redefining the covariate matrix. Also, the reference cell type needs to be specified in this step.
The scCODA model
sccoda.util.comp_ana.CompositionalAnalysis sccoda.model.scCODA_model.CompositionalModel sccoda.model.scCODA_model.scCODAModel
Utility functions
sccoda.util.helper_functions.sample_size_estimate
Executing an inference method on a compositional model produces a sccoda.util.result_classes.CAResult object. This class extends the InferenceData class of arviz and supports all its diagnostic and plotting functionality.
sccoda.util.result_classes.CAResult
sccoda.models.other_models contains implementations of several compositional methods frm microbiome analysis and non-compositional tests that can be used for comparison.
sccoda.model.other_models.SimpleModel sccoda.model.other_models.scdney_model sccoda.model.other_models.HaberModel sccoda.model.other_models.CLRModel sccoda.model.other_models.TTest sccoda.model.other_models.CLRModel_ttest sccoda.model.other_models.ALDEx2Model sccoda.model.other_models.ALRModel_ttest sccoda.model.other_models.ALRModel_wilcoxon sccoda.model.other_models.AncomModel sccoda.model.other_models.DirichRegModel sccoda.model.other_models.BetaBinomialModel sccoda.model.other_models.ANCOMBCModel