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Efficient Flow Cytometry Analysis & Sharing of High-Complexity Data Doesn’t Have To Be Complicated

The field of flow cytometry has entered the era of machine learning-assisted data analysis. Cytobank flow cytometry analysis software enables comprehensive visualization and analysis of single-cell data with no need for coding knowledge.

REDUCE VARIABILITY AND SAVE TIME BY AUTOMATING YOUR GATING STRATEGY

Cytobank Automatic gating streamlines population identification in two easy steps

Is manual gating a source of variability in your single-cell data analysis? Do you spend too much time on manually adjusting gates?

Join the Cytobank platform and find out how to train an automatic gating model using your marker panel and gating strategy, apply it to new data to faithfully identify the populations you defined without wasting time and effort on manual gate adjustments, and share it with others.

Cytobank automatic gating

Variabilité réduite par rapport au gating manuel

96 technical repeats were analyzed by four independent operators. An automatic gating model was trained on a subset of files (n=24) analyzed by operator 1 and subsequently applied to the remaining files by all four operators.

Reduced variability compared to manual gating

Shorter time to result

Time required for training and application of automatic model is 75% shorter compared to manual gating of the full dataset for population identification in 72 files with 7 gates.

Cytobank Shorter time to result
Cytobank Upload transform

Machine-learning assisted, cloud-based data analysis

 

The Cytobank platform is an easy-to-learn cloud-based solution for high-dimensional data analysis, and a reliable tool for visual data management and controlled sharing. And although your flow cytometry datasets might be complex, using Cytobank to analyze them doesn’t have to be.

Cytobank Analyze visualize

Dimensionality Reduction and Clustering Algorithms for complex biological data

 

In the Cytobank platform you will get access to tools for a complete workflow, starting from data transformation and fluorescence compensation, classical population identification via biaxial gating, to comprehensive population analysis with machine learning-based algorithms like UMAP, opt-SNE, t-SNE CUDA, viSNE, SPADE, FlowSOM and CITRUS.

Cytobank store collaborate

Secure access to the cloud and easy sharing to collaborate across the world

 

Share and access data anytime, anywhere from any web-enabled device. Cytobank platform’s cloud-based capabilities allow scientists from around the globe to collaborate and dive deeper into large and complex data sets.

Our Application Scientists will help you get the most out of your data. Our support team provides personalized support, training or even customized projects.

Unsupervised analysis and organized environment to improve reliability of results

Machine-learning assisted analysis

Cut off biased manual steps like manual gating and keep raw data and results connected and organized in one single place. The Experiment Manager will help you keep track of what has been done to your data and Sample Tags will expedite the creation of meaningful figures comparing experimental variables present in your dataset.

Highlights of the Cytobank platform

Citrus

A two-step algorithm that automatically subsets single-cell data then identifies statistically significant differences among groups of samples, taking prior knowledge into account. CITRUS is ideally suited to access the statistical prediction power of biomarkers.

Citrus
FlowSOM

Unsupervised Clustering

SPADE or FlowSOM to cluster phenotypically similar cells in a simple-to-interpret minimum spanning tree for fast, intuitive analysis and presentation of large high-dimensional datasets.

Dimensionality Reduction

The Dimensionality Reduction Suite in the Cytobank cloud allows you to select among four different algorithms for creating a two-dimensional view of high-parameter data. You have the choice among viSNE, UMAP, tSNE-CUDA and opt-SNE to help you quickly identify interesting or rare biological subsets in your samples.

Dimensionality reduction

The DROP function allows you to run the same algorithm on any type of data that comes in a tabular format.

Testimonial: What a user says about Cytobank

Learn how Hervé Luche, PhD, Scientific Head of the Immunophenotyping Module of the Center for Immunophenomics in Marseille, France, uses Cytobank to facilitate high-dimensional analysis of mass cytometry data sets. Watch his insightful testimonial here:

Choose the Option that Best Fits Your Needs

Cytobank Premium

Ideal for individual users and small labs.

  • Private account on a shared cloud
  • Free training with our Application Specialists to get you started
  • Support from a global team with expertise in biological data analysis

Cytobank Enterprise

Ideal for pharma/biotech and academia.

  • Administrator dashboard to manage all your users and data
  • Dedicated computing resources for your organization
  • Fully customizable for Enterprise integration in local applications
  • Personalized training and implementation support
  • Option for SSO & more storage space

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