Tool:For anyone struggling with messy single-cell data, CyteType is worth a look

Question

[sukhitha.basnayake]

I have been recently using CyteType while re-annotating a merged public dataset together with some of our own data, and it’s honestly one of the most interesting things I’ve tried in a while.

It looks at both supporting and conflicting markers, checks pathway context, and even rejects a label if the signal doesn’t make sense. In my case it caught a small cluster that turned out to be ambient RNA and low-quality debris, which every other tool labeled as microglia.

What’s neat is that it shows the reasoning behind each annotation, so you can see exactly how it reached a call. They’ve just put out a preprint explaining how their multi-agent system works across datasets. If you spend time cleaning or re-annotating complex single-cell data, it’s definitely worth a look.

Answer 1

[Kevin Blighe]

Hey, is this basically an ad for CyteType, or just your honest take? - kind of reads like promo, but if it's real, fair enough.

Sounds useful - I dig how it spots crap like ambient RNA that gets tagged as microglia by other tools, and lays out the logic. Kinda like cross-checking pathways in DESeq2 runs I've done.

You pair it with Harmony for batch stuff? Got that preprint link? On packages, bump to Seurat 5.3.1 or Scanpy 1.11.5 if you're behind.

Dataset size or what else you tested it against? Up for chatting through tweaks.

Kevin

[theodore]

He appears to be one of the authors.