Scalable multi-sample single-cell data analysis by Partition-Assisted Clustering and Multiple Alignments of Networks
Fig 8
Resolution of batch effects for simple batch effect scenario.
Network alignments allow the resolution of mean shift batch effect. (a) Resolution of batch effect by networks of all subpopulations discovered. In the left panel, the colors denote subpopulations that are aligned by network structures. The overlapped subpopulations are correctly labeled. The right panel shows the hierarchical clustering of the subpopulations’ networks via Jaccard dissimilarities. These subpopulations are the same as those in Fig 7. (b) Resolution of batch effect by marker levels. Alternative to alignment by network, marker levels (subpopulation centroids) can be used. However, the overlap of the different subpopulations from the two samples makes it impossible to resolve the mean shift in this simulated data. The hierarchical clustering of the centroids organize the subpopulations differently than that in part (a).