Mark Robinson and Charlotte Soneson have created the great conquer
dataset, which contains MultiAssayExperiments
R objects for about 38 single cell experiments with count level and consistently normalized data plus QC reports. Here is a gist which contains a python script (and conda requirements file) to pull down all those datasets.
This data was aggregated for use in: Bias, robustness and scalability in single-cell differential expression analysis.
Once you've downloaded the datasets, you can easily load them into R:
library(MultiAssayExperiment)
library(SummarizedExperiment)
data <- loadRDS("{dataset}.rds")
For a more extensive example, see the tutorial section on the conquer
site.