May 24, 2017  |  Announcements

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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May 10, 2017  |  API, Cytobank, User Stories

Two Disciplines, One Analysis Pipeline:
Leveraging the Cytobank API to Find Biological Insights

This week we interview scientists from two different disciplines to hear how they worked together and used the Cytobank API to develop an automated pipeline to find biomarkers for several chronic Graft-versus-host disease (GVHD) outcomes.  We asked bioinformatician and Cytobank consultant Ashu Sethi to share with us her experience using the API, and Cytobank’s own Hannah Polikowsky, on behalf of Vanderbilt, how this pipeline improved her analysis workflow.

AshuHannah2 More »

August 31, 2016  |  Announcements, API, Cytobank, Release Notes

Streamline and Automate Analysis with Our New API

CytobankAPIAchieve better results, faster. Automate your end-to-end pipelines with the Cytobank Platform via The Cytobank APIThe Cytobank API extends the power of the Cytobank Cloud to any software application. Now bench scientists can more seamlessly interact with computational biologists and reviewers to assess results of internal algorithms and pipelines. 

Now available in the Enterprise versionour RESTful API endpoints offer powerful advantages More »

June 20, 2014  |  Uncategorized

Population Sunbursts: Dynamically interact with population hierarchies and statistics

Communicating population relationships and associated statistical data is a fundamental aspect of single cell data analysis. A common method of communicating population relationships is via data tables that list populations and statistics. However, this becomes cumbersome as researchers work with higher dimensional experiments and complex gating strategies. To address this challenge, we’ve added a Sunburst Visualization that allows users to visually communicate population hierarchies. 

Think of a Sunburst as a radial tree where ‘wedges’ represent populations. The root of the tree in the center, descendants expand outward as slices of concentric rings, and each ring represents a level of your hierarchy. The size of a wedge is proportionate to the number of events in the population, and mousing over any wedge reveals statistical information.  Users can start with a global view of their gating hierarchy and then interactively drill down to the subsets in which they are interested.

The Sunburst visualization is available on Premium and Enterprise Cytobank sites, at the bottom of the gating page.

April 30, 2014  |  Cytobank

FCS File Quality Control Validation

With the recent rise in cytometry data post-processing (e.g., normalization, debarcoding, concatenation), we at Cytobank have seen many FCS files that do not conform to the ISAC specification, and some of these variations in file writing may lead to downstream errors. As a result, we’ve implemented a Quality Control validator, built into Cytobank, that determines the compliance of your FCS files compared with the specification.

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April 22, 2014  |  Education

The analysis challenges of high dimensional cytometry

With the rise in high dimensional cytometry, the need for new ways of managing and analyzing this information is essential. The Cytobank approach and platform led to several key publications in this area. As a result, we were invited to contribute a chapter published in Current Topics in Microbiology and Immunology. This chapter highlights the needs for new approaches to work with high dimensional cytometry and uses the Cytobank platform as an example of addressing the challenges. In addition, we also provide some practical ways of using algorithms such as SPADE to analyze datasets.
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April 21, 2014  |  Cytobank

Introducing the Cytobank Webinar Series

Greetings Cytobank community!

We have launched a weekly webinar series designed to give you an overview of Cytobank functionality, where you will have the option to ask your burning Cytobank questions. We’ll present a brief overview of the platform in slide format, and then walk you through the analysis of an actual dataset using Cytobank. You’ll have the opportunity to privately ask your questions via the webinar chat box and we will address them at the end. The series will be on an alternating weekly schedule where we rotate covering basic analysis and advanced topics such as SPADE.

View the schedule of upcoming webinars on our Upcoming Meetings page.

– The Cytobank Team

February 28, 2014  |  User Stories

Cytobank User Stories: Olga Ksionda, Ph.D.

Welcome to Cytobank User Stories, a series featuring interviews with Cytobank users on their research, scientific vision, and use of fluorescence and mass cytometry. This time we interview Olga Ksionda, Ph.D., a postdoctoral scholar in the lab of Jeroen Roose in the Department of Anatomy at the UCSF School of Medicine. Send us feedback and let us know who you’d like to hear from (including yourself)!

What are you excited about in science? What is your scientific vision?
Olga Ksionda, Ph.D.
Olga Ksionda, Ph.D.
UCSF School of Medicine

I am very much interested in understanding the molecular aspects of T cell development, especially in pathological settings when wrong decisions are “made” and T cells become autoimmune or malignant.

In general terms, I have always found it fascinating when unrelated fields cross fertilize with unexpected outcomes. I consider some of the best examples of this the Cre system or recently described CRISPR technology.

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