Get Started Quickly with Cytobank Basics
- How to get started with your data (experimental manager, upload/clone experiment, set scales and compensate)
- How to gate in Cytobank (draw, tailor, check, add and remove gates and populations)
- Overview of the Illustration Editor (create and modify figures, clone existing figures for additional modification, exporting illustrations, use templates to create a new figure)
- Introduction to overlaid figures (create colored overlay plot using different gated populations or conditions, overlay manually gated populations onto a viSNE plot, export table of statistics)
Ensure Reproducibility, Enable Collaboration and Accelerate Discovery
With the information provided in this page you will get an overview of capabilities of the Cytobank platform and get started quickly with analyzing your own data.
The analysis of flow cytometry and other single cell data requires a number of steps, such as compensation and other pre-processing tasks, gating and data visualization in different plot types as well as the export of statistical results for further analysis and graphing. This is typically done manually by individual researchers who may even use different tools for each of these different steps. As a result, the connection between primary data and final presented results is often not immediately obvious.
The Cytobank platform was specifically designed to address this challenge. For data analyzed on the Cytobank platform, it is always possible to drill down from a publication quality figure to the underlying primary data, thus ensuring that important knowledge on how scientific conclusions were drawn is retained, securely stored and documented.
The Experiment Manager on the Cytobank platform offers an interface that supports users in navigating their data by options to sort, filter and tag experiments. Linked experiments can be visualized in a tree-like hierarchy, enabling researchers to find related experiments quickly and to easily grasp the sequence of an analysis workflow.
International collaboration has become a driving force for scientific innovation. The Cytobank platform enables researchers around the globe to share their data and to collaborate on data analysis. Experiments can be grouped into Projects and collaborators can be assigned custom access permissions. Sample tags provide important contextual information that is accessible to everyone working on a data set and is no longer buried in individual lab notebooks. Additional information such as experimental protocols or results from other methods can be attached to the experiment on the Cytobank platform to create a central information repository.
In this video you can learn how to get started uploading your data, setting up scales, compensate your data and utilize the experiment manager to navigate trough the different section of the experiment or to share your data.
Dynamic Figure Generation for Complex Data Sets
One of the main differentiators the Cytobank platform offers when it comes to the creation of figures from complex experiments, is the use of sample tags to generate dynamic visualizations of results. Sample Tags become variables within the Illustration Editor. These variables can be toggled on or off and rearranged dynamically to build and modify a figure. This allows one to work above the level of FCS file names, and instead use the scientific variables that were present in the experiment, to build a figure while retaining transparent access to the underlying experiment annotation and data processing steps.