September 22, 2011  |  Flow Cytometry

Deconvolute, Decode, Decipher! How to Split, Tag, and Analyze Your Barcoded Data on Cytobank

You may have heard about Fluorescent Cell Barcoding, a flow cytometry technique that allows researchers to answer a larger number of questions with the same amount of antibody, as compared to standard flow cytometry experiments [1,2]. We’ve prepared a few resources to help you learn about, perform, and analyze barcoding experiments.


How does barcoding work? In the barcoding step, samples treated under different stimulation conditions are labeled with concentrations of dye that increase at a defined interval. The use of this dye to barcode effectively means that one cytometer channel is taken up for this code. The distinctly stimulated and labeled samples are then combined into one tube and stained with antibodies against targets of interest. This single tube is then run on a flow cytometer and data are collected for analysis. The most common approach is to barcode different stimulation conditions; however, barcoding can be applied to any distinct populations, such as patient samples or different time points of a stimulation condition.

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September 7, 2011  |  Flow Cytometry

Analyzing Hematopoietic Stem Cell Enrichment Data in Cytobank

Dataset #8414: Human Cord Blood – HSC isolation


Hematopoietic Stem Cells (HSCs) give rise to all blood lineages and are capable of self-renewal. Clinically, HSC transplantation is under investigation for the treatment of diseases of the blood and bone marrow, including cancer, where a patient’s blood cells are wiped out and replaced with healthy cells that arise from transplanted donor HSCs. Transplant studies in mice have shown that only a few of these cells are necessary to repopulate the entire hematopoietic system.

Human umbilical cord blood is a rich source of stem cells, including HSCs. However, a variety of other cell types populate cord blood and must be removed from HSC preparations used for transplantation. Multipotent progenitor cells (MPPs) are one such population. Derived from HSCs, MPPs give rise to multiple lineages and are present in significant quantities in cord blood, though they are limited in their capacity for self-renewal. Purification of HSCs can be achieved by staining and running cord blood through a FACS sorter and isolating cells with a Lin-CD34+CD38-CD90+CD45RA- surface signature (as defined by Park, Majeti, and Weissman). MPPs can be quantified or isolated by their Lin-CD34+CD38-CD90-CD45RA- signature.

Sample Data

If you would like to try your hand at analyzing HSC enrichment data on Cytobank, we have made available an HSC dataset provided to us by scientists at BD Biosciences. You can find a tutorial to guide your analysis on our documentation site. More »

July 21, 2011  |  Flow Cytometry

Naming and Exporting Files in Diva

Many of our users upload data to Cytobank that were collected on a BD Biosciences flow cytometer using BD FACSDiva™ software. In this post, we will walk you through how to harness the power of naming files in Diva to facilitate analysis on Cytobank and how to export FCS files from Diva for upload to Cytobank.

Detailed naming of sample files in Diva gives you a special advantage unique to Cytobank’s analysis environment. When you upload files to Cytobank, our servers will automatically categorize your files for ease of analysis when you annotate Figure Dimensions. This automated categorization enables you to rapidly generate well-annotated plot layouts and figures. Watch our YouTube video demonstrating this feature!

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June 10, 2011  |  Flow Cytometry

Working with Accuri Data

Cytobank users have uploaded and analyzed data collected from more than 30 different flow cytometer models, so chances are that Cytobank can handle your data! In a recent post, we featured the ability of Cytobank to facilitate the mining of data from large datasets generated by the DVS Sciences CyTOF. This time, we will walk you through analysis of data collected on the Accuri cytometers using their CFlow software.

Image plots from Accuri CFlow

Accuri provided us with a set of sample files demonstrating the collection of data from cells stained with a PE-anti-CD4 antibody, and we’ll use this as an example. You can see from their CFlow software analysis that they achieve separation of and gate on the lymphocyte population (P1, first panel), and further separate CD4+ from CD4- cells (second two panels). We’ll show you how to do the same in Cytobank!

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