API¶
Singlet analysis is centered around the Dataset class, which describes a set of samples (usually single cells). Each Dataset has three main properties:
- a CountsTable with the counts of genomic features, typically transcripts
- a SampleSheet with the sample metdata and phenotypic information.
- a FeatureSheet with the feature metdata, for instance alternative names and Gene Ontology terms.
At least one of the three properties must be present. In fact, you are perfectly free to set only the feature counts or even, although may be not so useful, only the sample metadata. Moreover, a Dataset has a number of “action properties” that perform operations on the data:
- Dataset.correlations: correlate feature expressions and phenotypes
- Dataset.feature_selection: select features based on expression patterns
- Dataset.dimensionality: reduce dimensionality of the data including phenotypes
- Dataset.cluster: cluster samples, features, and phenotypes
- Dataset.fit: fit (regress on) feature expression and metadata
- Dataset.plot: plot the results of various analyses
Supporting modules are useful for particular purposes or internal use only:
- config
- utils
- io
