May 20, 2011  |  Announcements, Flow Cytometry

What is SPADE?

What is SPADE?

SPADE (Spanning-tree Progression Analysis of Density-normalized Events) is a way to automatically identify populations in multidimensional flow cytometry data files. SPADE clusters cells into populations and then projects them into a tree like the one shown below. SPADE works for data from both ‘classic’ fluorescence flow cytometry and mass cytometry.

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February 23, 2017  |  Education, Flow Cytometry, viSNE

Five Key Takeaways from Our Latest viSNE Webinar

We recently hosted a very popular webinar, “Placing viSNE in Your Toolbox” featuring special guest Dr. Anna Belkina of Boston University School of Medicine. More than 500 investigators registered for our event to learn about cutting-edge tools and techniques for optimizing results from high-dimensional cytometry datasets.

Cytobank screenshots from Bendall et.al. Science 2011
Cytobank screenshots on Bendall et.al. Science 2011 data

Missed our latest viSNE presentation?
View the webinar recording here:
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January 11, 2017  |  Announcements, API, Cytobank

New API Enhancements: 4 Sample Workflows for Advanced Analysis

Cytobank has released version 5.5.0 with enhancements to our API, enabling more flexible and functional workflows that leverage Cytobank’s secure infrastructure and cloud-based compute and storage. Among the enhancements are new API endpoints for viSNE, CITRUS, SPADE, sharing, Sample Tags, and compensation.

At Cytobank, we’ve seen emerging needs among scientists and research organizations the world over that are driving the development of our API. These needs often demand functionality beyond that given by basic browser-based analysis sessions, with themes including connecting the Cytobank platform directly to other information systems, allowing batch processing and chaining of native functionality, and supporting pull and push of data, configurations, statistics, and attachments from Cytobank to support external pipelines, algorithms, and studies.

api-2_1-Fig-1a
Visual overview of the high level themes driving development of the Cytobank API.

In this article, we present a variety of workflows highlighting how the Cytobank API can increase the efficiency and velocity of research efforts. Illustrated workflows include:

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December 23, 2016  |  Announcements, Education, Publications

Our CEO’s Top Three Takeaways from the 2016 ASH Meeting

We were fortunate to attend the American Society of Hematology mhematology2016covereeting earlier this month in San Diego. It brought together leading clinical scientists to present and discuss advances in malignant and non-malignant hematology.

Since the Cytobank platform is used by many who attended and presented, we were proud to see and be a small part of the exciting science. Highlights for us were:

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October 4, 2016  |  Announcements, CITRUS, Cytobank, Release Notes

Fresh Squeezed News: Introducing CITRUS

Automatically Identify Predictive Biomarkers with Our Newest Algorithm

citrus-newsletterimage

Why do some cancer patients respond well to immunotherapy but others do not?

Why do some people have a slow and painful recovery from surgery but others have a speedy recovery?

What are the biomarkers that can help predict these outcomes ahead of time?  

The Challenge:
High-dimensional single-cell analysis approaches are excellent for investigating such questions because many mechanisms of disease may only be visible at the single-cell level, eluding bulk analysis techniques. Emerging technologies such as high parameter fluorescence and mass cytometry, and powerful data analysis platforms like Cytobank, are providing unprecedented resolution for measuring single-cell biology. With these new technologies, a variety of specific cellular populations can be simultaneously identified, and anomalies can define different clinically relevant cohorts and serve as predictive diagnostics and prognostics.

The challenge of going from high-dimensional data to these useful findings lies in the analysis, which is often cumbersome, manual, subjective, and irreproducible. Our new version of the CITRUS algorithm aims to change that. More »