Pretty comprehensive! But I think you are starting in the wrong end. Either go with what the clinic or pharma needs. Or look at at from an RNA perspective. Both approaches should converge on the percentage true/false positive signals, and true/false negative signals. Reliable data is the only thing the FDA will let through.
As example real single molecule RNA FISH - marketed as Stellaris RNA FISH by LGC Biosearch Tech - not the same as BioTechne/ACD RNAScope or ThermoFisher/eBioscience tree building RNA detection systems. The former uses non-signal amplification by laying our many singly labeled probes, the latter grows a couple of large DNA trees on top of the cellular RNA. The signals from the different modalities do not result in the same the percentage true/false positive signals, and true/false negative signals.
It would be very interesting to see what the percentages are for the others’.
Cool, I wrote something like this but not as comprehensive a while back https://open.substack.com/pub/weeklybioinformatics/p/peering-through-the-tissues-1?utm_source=share&utm_medium=android&r=1nz9t4
Pretty comprehensive! But I think you are starting in the wrong end. Either go with what the clinic or pharma needs. Or look at at from an RNA perspective. Both approaches should converge on the percentage true/false positive signals, and true/false negative signals. Reliable data is the only thing the FDA will let through.
As example real single molecule RNA FISH - marketed as Stellaris RNA FISH by LGC Biosearch Tech - not the same as BioTechne/ACD RNAScope or ThermoFisher/eBioscience tree building RNA detection systems. The former uses non-signal amplification by laying our many singly labeled probes, the latter grows a couple of large DNA trees on top of the cellular RNA. The signals from the different modalities do not result in the same the percentage true/false positive signals, and true/false negative signals.
It would be very interesting to see what the percentages are for the others’.