Single-cell phenotyping is critical to the success of biological reductionism. Raman-activated cell sorting (RACS) has shown promise in resolving the dynamics of living cells at the individual level and to uncover population heterogeneities in comparison to established approaches such as fluorescence-activated cell sorting (FACS). Given that the number of single-cells would be massive in any experiment, the power of Raman profiling technique for single-cell analysis would be fully utilized only when coupled with a high-throughput and intelligent process control and data analysis system. In this work, we established QSpec, an automatic system that supports high-throughput Raman-based single-cell phenotyping. Additionally, a single-cell Raman profile database has been established upon which data-mining could be applied to discover the heterogeneity among single-cells under different conditions. To test the effectiveness of this control and data analysis system, a sub-system was also developed to simulate the phenotypes of single-cells as well as the device features.
Keywords: Data analysis; Database; High-throughput; Raman-activated cell sorting (RACS); Simulation; Single-cell.