The problem. Once you have BANKSY, and a dozen other spatial-domain and niche-identification methods, the same question that hit deconvolution returns: which one do you trust, and under what conditions? Domains are fuzzier to score than cell types — there’s rarely a clean ground truth — so a careful benchmark is badly needed.

The idea. This is a systematic comparison of niche/domain-segmentation methods across datasets and platforms, scoring how well each recovers known tissue structure and how sensitive each is to the choices that matter — resolution, neighborhood scale, number of domains. The useful output, as with the good benchmarks, should be conditional guidance rather than a single winner.

Why it matters. This is exactly the flavor of paper a standards-minded facility values: not a new tool, but a map of when the existing tools work. Pairing a method paper (BANKSY) with its benchmark is the “know why, not just which” discipline I keep coming back to — it’s what turns a preference into a defensible recommendation.

Verdict. This is a very recent 2026 preprint, so I’m reading it purely for its purpose and framing and deliberately not repeating specific rankings or numbers until it’s peer-reviewed and I’ve read it in full. Flagged as the most speculative entry in this batch — verify everything against the manuscript before citing.