Posts filed under ‘Flow Cytometry’
Designing a successful flow experiment – selecting compatible reagents and optimizing your protocol – can be challenging and time-consuming. And yet, as we all know, a well-designed experiment is critical to the collection of high-quality flow data.
What do we think about when designing flow experiments?
- What buffers should I use when probing intracellular targets?
- Which surface antibodies work well on my sample and with my buffers?
- What is the best concentration for my antibody?
- Are there alternative protocols that work better with my samples?
We are excited to announce the arrival of two resources that will help you answer those questions and streamline your reagent selection process. BD Biosciences has released the FACSelect™ series, consisting of a Multicolor Panel Designer and a Buffer Compatibility Resource.
Are you working with a collaborator who needs to see your raw data? Are you looking for help from a Cytobank administrator relating to experiment analysis?
Don’t bother opening your email client, searching for an email address, and digging through folders for your flow files. Instead, use the easy sharing features built into Cytobank. Once you have uploaded files to your account, they can be easily shared with others from within the Cytobank interface.
As always, your experiment is visible only to you until you actively choose to give permission to another user to see it. When you do choose to share an experiment, follow these easy steps:
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.
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!
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.
Mass cytometry, a technique developed by DVS Sciences, now a Fluidigm Company represents a revolutionary spin on classic fluorescence-based flow cytometry. Instead of using antibodies tagged with fluorophores (in which spectral overlap quickly limits the number of parameters available for simultaneous detection), mass cytometry relies on antibodies tagged with transition element isotopes. Antibody-bound cells are vaporized, ionized, and analyzed on a mass spectrometer.
At Cytobank, we do cytometry in the “cloud”. What does that mean and how can that help you?
- Surviving the Data deluge
- Clarity, Access, and Collaboration
- Security and Back-up