Head: Leon HWANG
Email: leon_hwang@immunol.a-star.edu.sg
Manager: Ivy LOW, SCYM (ASCP)CM
Email: Ivy_Low@immunol.a-star.edu.sg
Flow
Cytometry Services
Operators: Salanne LEE
Email: flowcytometry@immunol.a-star.edu.sg
For booking and rates, please visit our Services page here.
For more
information regarding the SIgN Flow Cytometry Platform and services, please download a copy of our
brochure here.
The SIgN Flow Cytometry Platform is an established, state-of-the-art facility that uses cutting-edge cell sorters and analyzers to identify up to 30 parameters for a single cell suspension.
Background
Flow cytometry is a popular technique that is utilized in many fields of biological research, thanks to its wide range of applications in clinical and research laboratories. Using this technique, various cellular properties can be readily identified by measuring the fluorescence levels of the fluorophore-labelled cells at varying wavelengths. These properties include the granularity and size of the cells, their fluorescent intensity and their cellular expression levels of a protein of interest. A huge advantage of flow cytometry is that it permits the analysis of a large number of cells within a short period of time, allowing for samples to be easily identified, quantified and incorporated into immunophenotyping pipelines.
Technologies
and Approach
Our Flow Cytometry Platform is one of the largest in South-East Asia, with dedicated technical support staffs available to provide guidance at each experimental stage, from initial study design and staining protocols, to cell sorting and data interpretation. Specifically, the Flow Cytometry Platform can achieve high-throughput analyses with its available five-laser flow cytometers, and can perform deep cellular phenotyping using up to 30 different colours (Figure 1). Our facility is supported by dedicated and skilled personnel who are SCYM(ASCP)CM certified, a unique certification dedicated to flow cytometry staff. In addition, the Flow Cytometry Platform is now ISO9001:2015 accredited. For more information on how the Flow Cytometry team is dedicated to improve the quality of data, please follow this link: http://www.research.a-star.edu.sg/research/7612/new-tool-to-clean-flow-cytometry-data

Figure 1: Cell populations clustered according to phenotypic similarity using the tSNE platform. Whole blood stained with 25 surface markers to discriminate 38 different cellular clusters. Data obtained at SIgN using the FACS Symphony.