Tools#
Any transformation of the data matrix that is not preprocessing. In contrast to a preprocessing function, a tool usually adds an easily interpretable annotation to the data matrix, which can then be visualized with a corresponding plotting function.
Embeddings#
Clustering and trajectory inference#
Feature Ranking#
Rank features for characterizing groups. |
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Filters out features based on fold change and fraction of features containing the feature within and outside the groupby categories. |
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Calculate feature importances for predicting a specified feature in adata.var. |
Dataset integration#
Map labels and embeddings from reference data to new data. |
Survival Analysis#
Create an Ordinary Least Squares (OLS) Model from a formula and the data object. |
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Create a Generalized Linear Model (GLM) from a formula, a distribution, and the data object. |
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Fit the Kaplan-Meier estimate for the survival function. |
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Calculates the p-value for the logrank test comparing the survival functions of two groups. |
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Calculate the P value indicating if a larger GLM, encompassing a smaller GLM's parameters, adds explanatory power. |
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Fit the Cox’s proportional hazard for the survival function. |
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Fit the Weibull accelerated failure time regression for the survival function. |
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Fit the log logistic accelerated failure time regression for the survival function. |
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Employ the Nelson-Aalen estimator to estimate the cumulative hazard function from censored survival data. |
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Employ the Weibull model in univariate survival analysis to understand event occurrence dynamics. |
Causal Inference#
Performs causal inference using the specified causal model and returns a tuple containing the causal estimate and the results of any refutation tests. |
Normalized Complexity Profile#
Non-negative CP (PARAFAC) decomposition of a 3D temporal layer. |
Cohort Tracking#
Track cohort changes over multiple filtering or processing steps. |