Purpose

At Arcadia, we’re interested in using spontaneous Raman spectroscopy as an agnostic, high-throughput tool for biological phenotyping. To implement this approach effectively, we evaluated a variety of Raman spectroscopy systems to determine which would best align with our research requirements. By testing the same research-relevant specimens across all instruments, we could directly compare their performance characteristics, including resolution, sensitivity, and signal-to-noise ratios under real experimental conditions. To facilitate data processing and characterization, we also created an open-source Python package, `ramanalysis`, to process, normalize, and help interpret the spectral data from different manufacturers. We hope that others getting started with similar systems can use this notebook and the open-source Python package associated with it to assist in their analyses. Our analysis has several caveats based on the acquisition parameters and samples we used, and as such, isn’t intended to generate a definitive ranking or absolute comparison of the instruments themselves.

The full notebook pub is available here.

The source code to generate it is available in this GitHub repo (DOI: 10.5281/zenodo.15029361).