I’m wrestling with my inability to decide (based partially on lack of ability to understand) whether mashing tons of data together is a viable strategy to predict important biological outcomes…
Especially because: (1) it’s actually not so much data relative to the numbers of cells involved in a typical response and (2) we really don’t understand a lot about what goes on at single cell level in a response.
We know about key genes and how they influence populations when deleted but only at the bulk level and there’s lots of ways you can get from point A to Z in such cases…
Then again I do think one can learn that inflammatory macrophages may be a predictor of more disease severity in infections or something like that for what it’s worth. And maybe that’s clinically really useful? Even if it’s not leading to a clear biological explanation
I still think more patients/subject, more cells and well designed well done FACS panels are the right way to approach that though. I find interpretation of an increase in genes without much known about their function is more confusing than anything…
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