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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April 11, 2018  |  Announcements, Conferences, Flow Cytometry

Announcing Cytobank’s Collaboration with Cytek Biosciences

We’rCytekLogoe excited to announce a new collaboration with Cytek, makers of the innovative CytekTM Aurora Flow Cytometer. Cytek’s Aurora and Cytobank’s next-generation analytics platform have united in their goal to make high-dimensional data and its subsequent machine learning analysis more accessible to more scientists.

  • Aurora’s unique optical design combined with spectral unmixing delivers quality, high-dimensional data where rare and dim populations can be easily resolved, regardless of sample complexity.
  • Cytobank’s algorithms simplify visualization and analysis of high-dimensional unmixed data and allow you to quickly share discrete insights from these data.

Here are two specific examples of how you can apply our combined solutions to enable faster, more highly-resolved discoveries: More »

March 13, 2018  |  Announcements, API, Education

Introducing Cytobank BridgeR: An easy-to-use R package for Biologists

imagesThe Cytobank API opens up our platform to workflows and creative use beyond native functionality to improve the efficiency and velocity of your research efforts. We are excited to enhance the usability of the Cytobank API with the release of BridgeR, an easy-to-use R package for biologists.

Experience working in R isn’t required.  Our step-by-step guide provides instructions on how to execute the API-leveraged workflows detailed in BridgeR. More »

June 8, 2017  |  DROP, Education

Maximize Your Insight with Machine Learning Algorithms
and NanoString® 3D Biology™ Technology

Courtesy: NanoString
Image courtesy: NanoString

Scientists across many therapeutic areas are striving to solve complex biological problems by measuring multiple analytes, thinking that together these data will power deeper discovery. However, analyzing these data independently is less effective and more time-consuming than analyzing them together. Cytobank’s new DROP feature allows scientists to apply machine learning algorithms to many data types, including these datasets, and to develop integrated insights quickly.

With bulk data, unsupervised machine learning algorithms on Cytobank can help you identify clinically relevant groups of samples by combining information from all of your markers at the same time. We’ll illustrate that here with Nanostring® 3D Biology technology, which simultaneously analyzes up to 800 SNVs, RNA, and proteins and phospho-proteins from the same sample. In this example, the assays used profile 104 SNV and small InDels, 192 RNA, and 28 total and phospho-proteins in 144 samples.

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May 24, 2017  |  Announcements, DROP

Coming Soon: Analyze More Data Types in Cytobank

Run Cytobank’s machine learning-based dimensionality reduction and clustering tools across additional data types beyond cytometry. Discover biomarkers and explore cellular interactions and clinical outcomes faster and more comprehensively leveraging the scalable compute and collaborative power of the cloud.

Measuring system-wide immune responses requires significant breadth and depth of data [123]. Cytobank will soon release functionality on its Enterprise-level platform enabling you to expand your analysis beyond cytometry to tabular single cell or bulk data including RNA, DNA, extracted imaging features, proteins (e.g. cytokine/chemokine, antibodies, cellular proteins), metabolomics, clinical features, and more.

Analyze Multiple Single Cell Data Types to Discover More:image1

Leverage the discovery potential of broader, agnostic data types such as genomics and transcriptomics. Then cross-validate and delve deeper into mechanism with proteomics.

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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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