Multicolour Flow Cytometry (MFC) has changed the field of biomedicine by serving as a diagnostic powerhouse for assessing health and disease.
This technique enables us to examine marker expression at the individual cell level that offers crucial insights into cellular characteristics. Additionally, by simultaneously measuring multiple markers on cells, Automated Flow Cytometry (MFC) allows for thorough analysis of various cell populations.
Challenges with traditional MFC data analysis
Traditionally, Multicolour Flow Cytometry (MFC) data analysis has relied on manual gating. This process involves selecting cells of interest based on single or dual-marker expressions.
However, manual gating is subjective, resource-intensive and can miss relevant cell populations expressing multiple markers. As the number of measured markers grows, manual gating becomes less practical.
There is an urgent need for more advanced data analysis techniques.
The need for advanced data analysis
Recognizing the limitations of manual gating, researchers have proposed multivariate methods for more comprehensive Automated Flow Cytometry (MFC) data analysis.
However, these methods come with their limitations. They can make it difficult to visualize co-expression patterns among multiple markers and compare new data to existing models.
ECLIPSE: identifying disease-specific cells
About Eclipse
Meet ECLIPSE (Elimination of Cells Lying in Patterns Similar to Endogeneity), an innovative point of view designed to overcome the limitations of traditional MFC data analysis.
ECLIPSE combines Simultaneous Component Analysis (SCA) with Probability Density Functions. SCA is sophisticated upgrade of Principal Component Analysis (PCA) customized for MFC data. This dynamic duo works to point and remove ‘healthy’ or ‘normal’ cells from patient samples.
Mission of Eclipse
ECLIPSE’s mission is to clarify data analysis by zooming in on cells that are key to immune responses. That enables the creation of more focused and insightful models.
ECLIPSE offers a deeper understanding of disease-specific cell profiles thanks to identifying and studying abnormal cells in individuals who differ from a state of homeostasis. This sheds light on the immune responses linked to various health conditions. This offers a wealth of knowledge for medical research.
Purpose of Eclipse
ECLIPSE’s purpose is to focus subsequent data analyses on immune response-specific cells, leading to more informative and targeted models.
By pointing and distinguishing abnormal cells in individuals outside of homeostasis, ECLIPSE allows the study of disease-specific cell profiles. This provides valuable insights into immune responses associated with various conditions.
Real-world applications: ECLIPSE in Action
ECLIPSE was put to the test with two different datasets to highlight its strengths:
- The first, known as the ‘LPS study,’ focused on MFC analysis of neutrophils in healthy people exposed to systemic endotoxin (LPS).
- The second set searched into the varied immune responses observed in asthma patients.
ECLIPSE proved invaluable in both examples, smoothing detailed representation of the immune responses linked to each scenario. It illuminated the unique cell profiles associated with each disease and emphasized the variability in individual reactions.
This displays its potential to increase our understanding of immune system dynamics.
In Conclusion:
