| Flow cytometry is a technique for cell characterisation that is popularly used
in basic and translational research for understanding, for example, how mutated
stem cells may confer therapy resistance to a tumour (1). Alternatively, cell
characterisation can be used to measure cell receptors during activation or as
a response to immunosuppressive drugs. A flow cytometer consists of a narrow,
hydrodynamically-focused stream of cells that pass and are interrogated by a light
source. The cells’ physical characteristics of size and granularity, as well as any
fluorescent labels attached in or on the cells, scatter the beam of light. Fluorescent
labels attached will then be excited, enabling the appropriate emission
characteristics to be measured in relative terms of fluorescent intensity.
Flow cytometer manufacturers have responded to the needs of
modern researchers by developing faster systems that can measure
more variables over shorter time periods for applications such as
detecting tumour cells in peripheral blood and examining different
aspects of stem cell differentiation. However, the ability of the
software that flow cytometers rely on to analyse and visualise the
rapidly rising tide of data now being generated has lagged way
behind these improvements in instrument technology. This article
examines some of the approaches that enlightened software
manufacturers are now taking to speed up and simplify data
analysis and support the revolution in flow cytometry research. |
