iFlowCyt Overview

Recent advances in flow cytometry (FCM) allow for distinguishing between increasing numbers of cell subpopulations in the same tissue sample. However, standard one-dimensional histograms and two-dimensional plots are insufficient to capture fully the multi-dimensional nature of FCM data even when attention is restricted to just one tissue sample. These difficulties compound in complex study designs. Alternative methods for analysis and visualization are necessary to harness the full power of FCM. Our overarching goal is to investigate the use of advanced computational and statistical methods that take advantage of the high dimensionality of FCM data, and ultimately to develop iFlowCyt, an integrated, interactive, internet-based software tool that implements these methods with a friendly user interface.

Self-organizing maps for automated gating

We are examining the use of self-organizing maps (SOMs) for exploring and clustering subpopulations of cells within tissue samples, and will extend to multiple tissue samples from individual patients. SOM can map multi-dimensional FCM data to 2 dimensions through the use of self-organizing neural networks and group similar cells together so that human experts can inspect and discover cell subpopulations across multiple channels simultaneously.

Statistical graphics for interpretion of gating results

We are assessing the use of alternative graphical methods for representing multi-dimensional data across individual tissue samples. If a sample is divided into multiple cell sub-populations, we use the wind-rose chart (WRC) to display simultaneously the percent of cells in each sub-population. However, as the number of sub-populations increases, the ability to differentiate the segments in one WRC decreases. Hence we will also examine the use of other methods (e.g., heat maps, mosaics, etc.) to display these data, both as percentages in sub-populations as well as absolute counts of cells in sub-groups.

Statistical methods for interpretation of gating results

We are investigating the use of compositional data analysis (CDA) for comparing cell subpopulations between groups of tissue samples. Since FCM data can be expressed as absolute counts of cells in various subpopulations as well as proportions, we need to examine tools that can address both types. We will examine CDA to examine the proportions of cells in various sub-populations, to estimate central tendency and variability in groups of samples, and to compare between groups of samples. We also investigate the use of other multivariate methods to examine simultaneously the absolute counts of cells in various sub-populations.

iFlowcyt software

iFlowCyt is our research prototype that is under development. It is an integrated, interactive, internet-based set of software tools that implement the studied methods. You are more than welcome to test our current release IFCSoft 0.4 and let us know if you have any questions or suggestions!