analyzing data from single-cell RNA sequencing

There's an interesting problem floating around biology circles: biologists sometimes want to study, say, the RNA is just one cell. As in, you don't have a bunch of cells and average the results, you just have one cell to take samples from.

Why would you want to use single-cell sequencing? Well, if you worry that you have different types of cells, or cells that have different purposes, then to distinguish between them and avoid averaging over all the different types of cells you'd want to look at one cell at a time.

What's difficult about analyzing single-cell sequencing data?

Averaging is a smoothing operation, so when you're looking at averages you can use some well-behaved models, like linear models. But without averaging, without smoothing, without the law of large numbers... you're left with sparse, noisy data. What model are you going to fit to that?