Table 2.

Immunophenotyping platforms

Platform	Number of Parameters	Throughput (events/second)	Scalability
Standard Flow Cytometry	Typically: 1–20 Maximum published: 30 [99]	Typically: 1000—10 000 Maximum: 100 000	Very high throughput permits acquisition of many events High-throughput systems allow efficient automated acquisition of large numbers of samples Costs are typically <$100/sample 1 Relatively small file size per sample 2
Spectral Flow Cytometry	Typically: 20–30 Maximum published: 43 [78]	Typically: 1000–3000 Maximum: 30 000	High throughput permits acquisition of many events High throughput systems allow efficient automated acquisition of large numbers of samples Costs are typically <$100/sample 1 Larger file size related to acquisition of full spectrum for each laser 2
CyTOF	Typical: 30–40 Maximum published: 47 [100]	Typically: 200–500 Maximum: 1000	Slower throughput requires extended acquisition time Costs are typically <$300/sample though samples may be barcoded and multiplexed to reduce batch effects, cost, and improve processing efficiency and staining consistency 1 Large mass data file size, which is subsequently converted to traditional FCS files 2
CITE-Seq & REAP-Seq	Typical: 30–40 Maximum published: 228 [101]	Not acquired in real time; typical experiments will only evaluate <10 000/sample	Very slow processing to data time. Cells require partitioning, followed by cDNA generation, library construction, QC and sequencing which can typically take several weeks. Costs are typically $1000s/sample, though samples may be barcoded and multiplexed to reduce batch effects, cost, and improve processing efficiency at the cost of total cells per sample 1 Very large sequencing data file size, often accompanied by scRNA-Seq data

¹Costs will be affected by number of antibodies. Isotope conjugation for mass cytometry increases costs/antibody.

²File size will be dependent upon number of events acquired.

The number of parameters required will vary based on experimental needs and reagent availability, cost, and in the case of flow cytometry platforms, marker coexpression.