Overview of the flowType/RchyOptimyx pipeline for identification of correlates of protection against HIV.

<p>First, tens of thousands of cell populations are identified by combining one-dimensional partitions (panel 1). The cell populations are then analyzed using a statistical test (and Bonferroni's method for multiple testing correction) to identify those correlated with the survival information. Panel 3 shows a complete gating hierarchy describing all possible strategies for gating that cell population. This graph can be mined to identify the “best” gating strategy (i.e., the one in which the most important markers appear earlier). These hierarchies for all selected phenotypes are demonstrated in panel 4. In panel 5, these hierarchies are merged into a single graph that summarizes the entire dataset and demonstrates the trade-off between the number of markers involved in each phenotype and the significance of the correlation with the clinical outcome (e.g., as measured by the <a href="http://en.wikipedia.org/w/index.php?title=Kaplan-Meier_estimator" target="_blank">KaplanMeier estimator</a> in panel 6). Figure reproduced in part from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003365#pcbi.1003365-Aghaeepour3" target="_blank">[49]</a> (public domain) and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003365#pcbi.1003365-Aghaeepour4" target="_blank">[50]</a>.