CCA finds a shared correlation structure betwen two different datasets, enabling integrated downstream analysis
MultiModal_CCA(object, assay.1 = "RNA", assay.2 = "CITE",
features.1 = NULL, features.2 = NULL, num.cc = 20,
normalize.variance = TRUE)Seurat object
First assay for multimodal analysis. Default is RNA
Second assay for multimodal analysis. Default is CITE for CITE-Seq analysis.
Features of assay 1 to consider (default is variable genes)
Features of assay 2 to consider (default is all features, i.e. for CITE-Seq, all antibodies)
Number of canonical correlations to compute and store. Default is 20, but will calculate less if either assay has <20 features.
Z-score the embedding of each CC to 1, so each CC contributes equally in downstream analysis (default is T)
Returns object after CCA, with results stored in dimensional reduction cca.assay1 (ie. cca.RNA) and cca.assay2. For example, results can be visualized using DimPlot(object,reduction.use="cca.RNA")