Even at warp speed, AutoGate gives you unmatched accuracy, relying on revolutionary breakthroughs in mathematics and statistics. Our "Density Based Merging" (DBM) algorithm determines the number and boundaries of your subsets. The Herzenberg Lab created DBM in a path-breaking collaboration with Stanford's world-famous Department of Statistics. No matter how many subsets you have, and regardless of whether they have a significant numbers of unrelated "outliers," DBM finds what you need to know.
DBM is non-parametric, seeing non-convex shapes directly and naturally. It detects irregular subset shapes and smears. It allows for variable subset density and frequency. It accounts for unclassified events in the background. It uses Fast Fourier Transform (FFT), making it computationally fast and stable. It avoids 'black box' output, allowing users to incorporate prior information.
Designed for both research and clinical use, AutoGate matches samples and quantitatively compares them by using robust algorithms called "Weighted overlap comparison" (WOC) and "Earth-mover's distance" (EMD). Instead of wasting your time drawing gates by hand, which is arbitrary and subjective, you can use AutoGate to gate your subsets for you. Nowhere will you find gates so precise, accurate, and inclusive. See for yourself.
Apply your gating models to new experiments. Use your gates to expedite clinical trials. Simplify statistically valid "before and after" studies, such as those needed in HIV testing, vaccine trials, and the monitoring of clinical care.
Rely on AutoGate's quality control, which operates at a far higher level than flow cytometry has ever known. Whenever the program detects severe problems with compensation samples or the creation of the matrix, it terminates its calculations and issues a report describing the problems. When AutoGate detects lesser problems, it warns you and lets you move on to gating. A description of the problems will accompany your compensated data.
Graphically, AutoGate displays your data in a unique "hyper-Node" tree structure. This gives you organized access to your compensated data and to the subsets that the automated analysis enables you to define step by step.
For each node in the tree, you can switch back and forth between a brief verbal description and several types of mini-displays of your axes and subsets. Clicking on the node brings up a full-size display of the clustered data, enabling you to further analyze the clusters and progressively add new information to the node.
AutoGate gives you all this, and does it in a way that is easy to learn and easy to use. No other software offers you anything close.
A beta version of AutoGate is currently available without charge to researchers and clinicians with academic (.edu), government (.gov), and non-profit (.org) emails. Try it. Surprise yourself by how much faster, easier, and more accurate flow cytometry can be.