This tool can be used toc ombine two Seurat objects for later joined analysis.
As inputs, give two Seurat object generated with Seurat Setup tool.
NOTE: make sure you have assigned the sample or group name in the Setup tool (use short names like "CTRL", "TREAT"). This name will be used later on to separate the samples.
This tool performs data integration to two samples (in .Robj). First, Canonical correlation analysis (CCA) is performed to identify common sources of variation between the datasets. The tool then identifies anchors, gives scores (=weights) to these anchors and then uses these anchors to integrate the datasets.
The first parameter tells which dimensions from the CCA to use for specifying the neighbor seach space. The neighbors are used to determine the anchors for the alignment.
The second parameter is the number of PCs to use in the anchor weighting procedure. The anchors and their weights are used to compute the correction vectors, which are used for correction, thus allowing the datasets to be integrated.
For more details, please check the Seurat tutorials for multiple sample analysis.
For more detailed description of the integration process, read "Comprehensive integration of single cell data the paper by Rahul Satija et al.