We have recently published a F1000Research workflow for low-level analyses of single-cell RNA-seq data:
It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. We demonstrate the analyses on public data sets involving haematopoietic stem cells, brain-derived cells, T-helper cells and mouse embryonic stem cells. We hope that this article will be helpful to members of the Bioconductor community who are working on scRNA-seq data.
P.S. Currently the workflow depends on packages from BioC 3.4 (i.e., BioC-devel, for the time being).