AutoGate's fully automated methods

Automate the classification and characterisation of flow cytometry data using full automation grounded on statistics, math and data science
+ recommended - regular updates and full support

MULTILAYER PERCEPTRON (mlp)

neural networks with MATLAB’S fitcnet & Python’s TensorFlow for a consistent assay-specific classifier.

unform manifold approximation and projection (umap)

produces a lower-dimensional representation of the data for data visualization and exploration

EXHAUSTIVE PROJECTION PURSUIT (epp)

designed to find subsets based on phenotyping markers and scatter parameters

RESULTS with AUTOMATED METHODS

COMPARISON OF AUTOMATED METHODS

AutoGate in the last 3 years has acquired 5 fully automatic gating methods. Two methods are unsupervised: Exhaustive Projection Pursuit (EPP) and Uniform Manifold Approximation and Projection (UMAP). Three methods are supervised: multilayer perceptron (MLP) neural network based on MATLAB fitcnet; MLP based on Python TensorFlow and UMAP supervised templates.

automated methods as a package

AutoGate Engine

The engine behind AutoGate’s automated methods (MLP, UMAP, EPP) and UMAP function published at Mathworks File Exchange ,is available to be downloaded as an independent package

VISUALIZATION TOOLS

Gating Tree
Plot Editor with 1D, 2D Pathfinder
Samples gated and analysed in AutoGate can now be called into FlowJo using the plugin we have developed. Click link to download.
Users can now use their google drive account to storage and retrieve analysis results from AutoGate. Click link for details.
Using this package, up to date reagent information from all leading reagent manufactures can be viewed. Click here for more
Reagent Genie
Reagent Catalogs

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