Feature request: add Nearest Neighbor Descent method

[Yunuuuu]

The R package is deposited here: https://jlmelville.github.io/rnndescent/index.html

[LTLA]

There are two possible approaches.

The first is to write knncolle wrappers around a hypothetical C++ library that implements the NN-descent approach. This would then be plug-and-play into BiocNeighbors with full compatibility across R and C++. I don't mind writing these wrappers, but it requires someone to first strip out the C++ code from rnndescent and make it work as a standalone library, see these old comments.

The second is to extend BiocNeighbors at the R level. This is easier and can be done by anyone, but precludes the use of NN-descent in C++ code across my other BioC packages. For example, you wouldn't be able to use NN-descent during MNN correction, or in SingleR, etc. Also, this would involve importing the rnndescent package, which I am reluctant to introduce to the BiocNeighbors dependency tree. I would prefer that it be written as a separate package that extends BiocNeighbors. In any case, I don't feel like doing this myself, so if you really like NN-descent, you may consider writing this package - see the BiocNeighbors vignette for extension instructions.

I also vaguely remember that NN-descent is intended for fine-tuning existing NN-search results, which complicates the situation. Should it be written as a "meta-algorithm" that requires another approximate search algorithm to generate the initial results? Something for the implementer to consider.

[Yunuuuu]

Thanks for the detailed explanation .

I actually gave the R-level implementation of NN-descent a try and attempted to wire it into BiocNeighbors, but I ran into some difficulties when integrating it with scran::correctmnn. Eventually, I gave up on this approach.

[Yunuuuu]

The UMAP based on the Nearest Neighbor Descent method is really elegant — it's the default in scanpy, though I’m not entirely sure if the beautiful results are purely due to the method itself. Either way, I’d love to have a similarly seamless experience within the Bioconductor ecosystem. That’s part of what motivated me to explore tighter integration of NN-descent, even if it’s been a bit tricky so far.

[LTLA]

I don't have much to say on the aesthetic value of these plots, but if you think it's a worthwhile goal, you should probably check if you can reproduce them with rnndescent and uwot first.

[Yunuuuu]

Thanks — I gave it a try, and it seems that the neighbors from rnndescent alone don’t fully account for the nice UMAP results. It looks like something else in the pipeline is also contributing to the final outcome. I’ll need to dig a bit deeper to figure out what’s going on under the hood.