In Single cell, once we perform a clustering, for example, "umap", which generate X number of clusters. Next is to perform annotation for cluster, which can be done by looking at differentially expressed genes within each cluster. if we get DEG within each cluster, are these DEGs the result of multiple cell comparison? I remember in bulk-RNA seq, we can only do two groups at a time using contrast? Not sure how do they compared to get DEG among several hundred cells in a cluster for single cell experiment?
Also, with integration of large dataset, the main purpose is batch correction etc. In the end, we get a single umap plot, which is the result of integration of all number of samples and conditions (control/treatment etc) from all groups. Does the display of a single "umap" mean that these cell clusters are found across samples and conditions? How could I know from a single umap that this/that group has less, for instance, fibroblast or T cell given I have cluster with with fibroblast or T cells etc. What is the point of displaying a single umap of all data set (I normally see this in publication)? Sorry I am just very confused... Looking to hear from you all.