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The power of multivariate data analysis in uncovering the nuances in complex data sets


LumaCyte's blog site for all news, information, featured stories, article reviews, and tech notes related to single cell analysis across many applications including Vaccine R&D and biomanufacturing, viral infectivity, bioreactor monitoring, neutralization assays, oncolytic vaccines, adventitious agent testing, phenotypic drug discovery, label-free biomarkers, anti-viral testing, gene therapy, CAR-T therapy, label-free single cell discovery and sorting.

The power of multivariate data analysis in uncovering the nuances in complex data sets

Sean Hart

Laser Force Cytology, the cutting-edge single cell, label-free technology powering LumaCyte’s Radiance instrument, has applications spanning viral infectivity, neutralization assays, immunotherapy (CAR T, TCR), anti-viral development, phenotypic drug studies, and stem cell studies. LumaCyte’s Radiance instrument, employs proprietary artificial cells for calibration that more closely mimic the properties and behavior of cells than do the solid core polystyrene beads typically used for particle measurement and calibration in other instruments. The video shows data from three different artificial cell types based upon polystyrene (PS) and polymethylmethacrylate (PMMA) but they are not solid beads and therefore have a lower refractive index that is much closer to mammalian cells, making them suitable for calibration in the Radiance instrument. The video shows a 4-dimensional graph where the axes are deformability, eccentricity, and velocity (proportional to optical force), and the size of each marker is proportional to the diameter of each calibration cell.

Observing the data from the initial two axes, deformability and eccentricity (the deviation of a cell’s aspect ratio from a perfect circle), one sees significant overlap in the data, but upon rotation to expose the velocity axis (proportional to optical force), one sees great separation not visible without the third dimension of data. Analyses that include four or even more dimensions of data are very instructive and enable the use of a wide variety of multivariate techniques including principal component analysis, partial least squares regression, and machine learning / artificial intelligence. 

The Radiance instrument gives users the opportunity to generate label-free single cell data to better understand their biological systems in new and powerful ways for R&D and biomanufacturing. When used for instrument calibration, multivariate data can result in more robust and powerful predictions of unknown samples.