What are you excited about in science? What is your scientific vision?

Sean Bendall, Ph.D. Postdoctoral fellow, Nolan lab Stanford University The thought of finding new biological paradigms is what gets me most excited.  There are many basic things in life that happen (biologically / biochemically – that is) which we take for granted.  However the underlying mechanism of many of these is completely unknown to us, and thus when they go awry we have little recourse to address them therapeutically.  Currently, in the context of the human genome, we really only have a grasp on about 20% of what’s there.  My overriding goal would be to develop methods / systems to help rapidly fill in this knowledge gap.  Because of the complexity (heterogeneity) of the human system, I believe that single-cell approaches will be best in addressing this and therefore my work will only put an increasing demand on analysis platforms to accommodate it.

What do you study / what is your field?

I study the function (behavior) of and develop methods for analyzing the different hematopoietic and pluripotent stem cell compartments.

What do you use flow cytometry for?

Everything?  When you deal with any sort of real sample that contains a complex mixture of cell-types or cells behaving asynchronously, single cell resolution is a necessary requirement for the analysis.  Flow cytometry is one of the most robust and rapid methods to accomplish this.

What are some of your favorite papers?

The first stem cell paper: A direct measurement of the radiation sensitivity of normal mouse bone marrow cells. Till JE, McCullough EA. Radiation Res. (1961) 14:213–222. Gold-standard phospho-flow: Intracellular phospho-protein staining techniques for flow cytometry: monitoring single cell signaling events. Krutzik PO, Nolan GP. Cytometry A. (2003) 55(2):61-70.

What do you do for fun?

Avoid writing emails.

What’s your favorite thing about Cytobank?

Heatmaps, exporting gated data, custom scaling of scales for data display, ability to “instantly” re-arrange an analysis (illustration) from an existing project.

Interview conducted and presented by Cytobank staff member Angela Landrigan.

Search our Knowledge Base

Our new support site has a Knowledge Base filled with articles to augment your Cytobank experience. You’ll find tutorials on our functionalities using real datasets, articles guiding you in both basic and advanced Cytobank usage, and answers to frequently asked questions. You can browse through article sections or conduct a keyword search of the Knowledge Base.

What kind of support can I receive from Cytobank?

We offer a wide range of support for your flow cytometry endeavors:

• One-on-one WebEx-based training to get you started using Cytobank
• Biology consulting support: How to design experiments, what to measure, selecting reagents, how to build figures, how to share datasets from your peer-reviewed publications
• Troubleshooting
• Data security
• Technical support for networks
• Inquiries about getting started with premium functionalities such as SPADE and dose response

Whether you need assistance using Cytobank or would like scientific input relating to experimental design or analysis, our support staff is here to help and will generally respond within 24 hours.

Visit our Chatroom

Another way to get immediate support is to visit our support chat room, generally open from 10am-6pm PST Monday-Friday. The link our chatroom can be found on the new support page.

Get updates on new functionality, protocols, and conferences

Visit our blog to learn about new Cytobank functionality and content related to flow cytometry experiments. Navigate the links at the top of the blog page to gain access to protocols sheets, handouts, and a list of conferences where you can find members of the Cytobank team. We attend many of the international, national, and regional flow cytometry conferences. You can subscribe to receive blog updates by email and subscribe to our Twitter feed on the right-side column of the blog page.

- Angela

Hosted models of Cytobank

You may be familiar with our main server at http://www.cytobank.org/cytobank/, but did you know that we can host an instance of Cytobank specifically for your lab group? With these hosted solutions, your lab manager or PI controls who has access to your server and can guide the group in configuring projects to keep various research branches well organized. Read our previous post on Projects to learn more about Projects. Hosted models of Cytobank also have the advantage of offering you premium functionality that isn’t available on our main server, such as SPADE and dose response.

Giving your lab manager or PI access by default

When you upload an experiment, you have the option to set the principle investigator (PI) on the experiment, which gives the PI full access to that experiment. In your particular lab, you may want to give more than one person access to every experiment you upload (perhaps your PI and lab manager). To do this, simply create a Project, give your lab manager and PI access to that Project, and then set it to be your “Default Project” under the Profile link at the top of the Cytobank webpage. Now, every experiment you upload will become part of that project, and your PI and lab manager will automatically have access. Giving your PI and lab manager access to your experiments is a great way to promote continuity and data-preservation in your lab.

Backup and keep all your data organized: protocols, presentations, microscopy, and more

Uploading your data to Cytobank, whether for storage, analysis, or sharing, is a great way to create a reliable backup for your data. In addition to backing up your flow cytometry experiments, our servers allow you to backup data of any type, and to associate those data with specific experiments. To backup and associate a protocol, presentation, microscopy image, or any other file type with one of your flow cytometry experiments, simply visit the Experiment Details page for that experiment and use the Attachments or Protocols section to upload additional filetypes. You can also upload experiments consisting of only non-FCS files by creating a new experiment and choosing to upload only those files.

Use our Inbox tools to efficiently manage and rapidly access your experiments

Now that you’ve organized your experiments into projects, attached related non-FCS files, and given your PI access to your data, have a look at some tools we offer to further organize and filter your experiments using the Cytobank Inbox. Read our previous blog post on Organizing Your Experiment Inbox.

Invite a colleague

Are you working on a collaboration, or alongside someone in your lab? Are your PI and lab manager looking to preserve data as people join and leave the lab? Make sure they have signed up for a Cytobank account so that you can easily share your data with them. You can use the “Invite” link at the top of the Cytobank webpage to invite colleagues to join. Now you’ll never have to email FCS files again, and instead can share well-labeled experiments and figures with the click of a button.

- Angela

Related Blog Posts:
Future-Proofing Your Experiments
Customized Sharing Using Projects
Never Email FCS Files Again
Organize Your Experiment Inbox
Cytometry in the Cloud

The Cytobank Story – Read about how the need for dynamic summaries of experiment results linked to the underlying single cell data resulted in the creation of Cytobank.

Cytometry in the Cloud – Advances in flow cytometry now enable researchers and clinicians to simultaneously measure a large number of cellular parameters. Learn about how doing cytometry in the cloud with Cytobank can accelerate data analysis, foster collaboration, and provide data back-ups.

Mass Cytometry: Vaporizing Cells in the Name of Science – Learn about mass cytometry, where antibodies are conjugated to element isotopes instead of fluorphores, increasing the number of cellular parameters that can be assayed in one sample tube. Access the raw data from a Nolan lab dataset published in Science this year, and try your hand at analyzing mass cytometry data yourself!

Future Proofing Your Experiments and Files: The Importance of Annotation – Learn how to annotate your sample files in ways that will accelerate your analysis. From sample collection on the cytometer to annotating files in Cytobank, associating descriptive details with your sample files will ensure your data are preserved for years to come.

Publications Referencing Cytobank – We are seeing publications emerging from around the world that have used Cytobank in their work, including publications in journals such as Science, Cell, Blood, The Journal of Immunology, and several others. Check out our new page listing publications referencing Cytobank and leave us a comment if we have missed any.

Additional Featured Posts:

How to Justify an iPad in Your Grant

5 Terms You Need to Know in Cytobank

Biochemistry at the Single Cell Level (Experiment protocol, video tutorial on analysis, hands-on sample dataset)

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

Visit our Newsletter Archive for additional posts.

- Angela

Public experiments and Archived experiments are flagged with "P" or "A," respectively.

The Experiment Inbox is the first page on which you land when logging into Cytobank. By default, you will see “All Experiments,” including public experiments (denoted with a ‘P’), experiments you uploaded, experiments shared with you, and your archived experiments (marked with an ‘A’). You can change your default inbox view on your Profile page (click the Profile link at top of the experiment inbox, and then click “Edit”), for example if you wanted to display only “My Experiments” every time you log in.

Experiment Filters

Experiment filters are an easy way to quickly narrow your inbox contents. If at any time you want to display a certain category of experiments that is different from your current view (for example, “My Experiments” only), simply click on that filter name in the blue “Experiment Filters” box. You can think of experiment filters like folders that contain only certain categories of experiments, and clicking on the filter name pulls up only those experiments. Mouse over the info card (the little “i”) in the upper right of this box to learn what each of the filters displays. (Note that we recently updated how these filters work.)

Inbox search box

Maybe you’re a power user, and even when you narrow your inbox to display only “My Experiments,” the list is still too long to scroll through manually. Well, there are several tools to help you quickly hone in on the experiment you seek! If you happen to remember any part of the experiment name, entering it into the “Search” box at the top of the inbox will further narrow the list of experiments to only those containing that search phrase. If you want to glance through your experiments by alphabetical experiment name, date modified, primary researcher or other such experiment details, just click the column heading and your experiments will be ordered based on the information in that heading (e.g., in order by date last modified). If you don’t tend to remember the details of experiment descriptors, then “Labels” may be for you.

Labels

Labels allow you to tag experiments based on a commonality among them – for example, you could label some experiments as “Human Experiments” and others as “Mouse Experiments.” You might already be familiar with this concept if you use Gmail. When you apply labels to experiments, the new label appears next to the experiment name and in the list of Labels on the left side of the inbox page. Clicking on a label name allows you to narrow down the experiments displayed in the inbox to ones possessing this label. You can also use the search box to search for experiments containing a certain label. You can add labels to experiments at any time, but we suggest using them from the beginning to avoid frustration when hunting for experiments down the road! Learn more about how to create and apply labels on our documentation site.

Projects

If you’re already familiar with Projects, Labels might sound conceptually familiar. That’s because you can also group experiments by creating and assigning experiments to a Project (and then clicking on the Project name to display only those experiments). The difference is that Projects allow you to specify other Cytobank users who can have access to those experiments and to specify their access level permissions. You can read more about this in our previous blog post on Projects.

Archive old experiments

Several users requested the ability to archive experiments they no longer frequently access, to clear the clutter out of their inbox while still ensuring their data would be around for future access. We heard your requests! You can now find an “Archive” button at the top of the inbox. Simply check the checkbox next to the experiments you wish to archive, and then click the “Archive” button. This will eliminate these experiments from the “My Experiments” view, and you can pull them up at any time by clicking the “Archived Experiments” filter.

Top Experiment Variables and Top Channels

Finally, you can use the Top Experiment Variables and Top Channels to display experiments based on experiment-specific parameters. The Top Experiment Variables section groups your experiments by the most commonly used experiment variable tags. In this section, you’ll see a list of your most commonly used Conditions, Timepoints, Doses, Individuals, and Sample Types, and you can click on these parameters to show only those experiments in your inbox. The Top Channels section likewise displays your most commonly used channel annotations. For example, maybe you have 50 experiments using pERK1/2; you can display only those experiments by clicking on the pERK1/2 link. Remember to future-proof your experiments by annotating your samples as you collect data on the flow cytometer! This will help automate the experiment variable tagging and channel labeling process on Cytobank and help you make use of these Inbox tools.

Save yourself time down the road when you need to revisit data or prepare presentations and publications – get a jump start on labeling and organizing your experiments now!

- Angela

CLONE EXPERIMENT

Choosing to clone an experiment makes a full copy of the experiment, complete with all FCS files, gates, annotations, reagent labels, compensation matrices, protocols, and attachments. Let’s suppose a collaborator has shared an experiment with you. You want to tweak the existing gates without having to redraw them entirely, but don’t want to overwrite the collaborator’s own gates. You can clone a full copy of the experiment and then make the changes in your clone, saving yourself the time that would have been spent redrawing gates and the headache of realizing you erased someone else’s hard work. From an organizational standpoint, you may also want to clone a copy of an experiment shared with you if you want a copy that contains only your own saved illustrations, notes, and attachments, including presentations.

With your own experiments, you might also want to make full clones if you want to subtly tweak existing gates or annotations to perform slightly varying analyses of your own data. “Clone Experiment” can help you do just that.

When you clone an experiment, the clone name contains "(Clone)" at the end, by default.

SELECTIVE CLONE

Selective Cloning allows you to choose subsets of FCS files to copy into a new experiment while specifying whether to bring over the gates, compensation matrices, annotations, reagent labels, protocols, and attachments – you can choose to copy over some or all of these components, helping you make copies of experiments that can be analyzed in different ways. Perhaps you want to preserve how files are categorized into Conditions and Timepoints, but draw gates from scratch for an alternative analysis – use Selective Clone to clone all files with all annotation, but no gates. Maybe you want to alter how files are categorized into Conditions and Sample Types, but want to preserve gated populations – use Selective Clone to copy all files and gates, but none of the annotations. Selective Clone can help you perform iterations of experiment analysis without having to start from scratch, whether on your own experiments or experiments shared with you.

You can also use Selective Clone to split off smaller pieces of a large experiment for separate analysis, or to separate files that require different annotation, gating, or compensation.

CLONE FCS FILES

There may be times when you want a completely fresh start, for example if you are using a dataset to teach flow cytometry analysis, or if you are a computational biologist trying to automate analysis. Clone FCS files is also useful if you want to share only the raw data with a colleague without sharing your analyses and other related information. By cloning FCS files only, you are copying the raw data into a new experiment without bringing over any gates, annotations, reagent labels, compensation matrices, protocols, and attachments that are associated with the original experiment.

Let us know if you have any questions about this functionality or any others!

- Angela

Background

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.

(Adapted from Krutzik and Nolan, Nature Methods 2006)

Performing the Experiment and Analysis on Cytobank

We’ve prepared a video tutorial that walks you through how to work with barcoded data on Cytobank (skip to 2:01 to jump straight to Cytobank analysis, if you wish). You can follow along by cloning your own copy of Experiment #8938. In this experiment, human PBMCs were stimulated with four stimuli, and two unstimulated conditions were included, resulting in the need to barcode such that these six sample types can be distinguished when combined into one tube. Two barcoding dyes were used to create a 3 by 2 barcoding matrix. We drew gates to define the barcoded populations, exported the gated data into separate FCS files, and proceeded with analysis as usual in Cytobank. In the exporting step, Cytobank computationally separates the barcoded cells into different files, as if you had never barcoded them to begin with. Then files are easily analyzed in standard flow cytometry packages, including Cytobank. Splitting off the barcoded cells into separate files dramatically reduces the processing power (and time) required to perform analysis in any software package.

For a condensed summary of how to work with barcoded data on Cytobank, see our text-based barcoding tutorial.

Additional Information

Want to learn more about the nuances of barcoding, such as how to choose barcoding dyes? Visit our Barcoding FAQ documentation. As always, you can submit a support ticket to request additional help by email or WebEx.

References

[1] Krutzik PO, Clutter MR, Trejo A, Nolan GP. Fluorescent cell barcoding for multiplex flow cytometry. Curr Protoc Cytom. 2011. Chapter 6:Unit 6.31.

[2] Krutzik PO and Nolan GP. Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling. Nature Methods. 2006. 3(5):361-8.

- Angela

Background

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.

Here are a few Cytobank features that will facilitate your analysis (click on the images to enlarge them):

View Populations

In the gating applet, you can view the gating hierarchy you have drawn by clicking View in the Populations box. Click the arrows next to the populations to reveal their descendents.



Gating Hierarchy

With the HSC and MPP populations selected in the Populations Figure Dimension, maximizing the Gating Hierarchy box in the Working Illustration will lay out the gating hierarchy, which directly corresponds to the FACS sort scheme used to isolate the cells.

Illustrations and Percent in Gate

Build an Illustration to compare pre-sort and post-sort samples, with the goal being to compare HSC purity levels. The Percent in Gate features enable you to display the percentage of cells falling within gates. In the example HSC dataset, we can see that HSCs were enriched from 43.05% pre-sort to 99.55% post-sort.

You can learn more about these and other features by viewing the HSC Isolation from Human Cord Blood analysis tutorial on our documentation site.

Forward Thinking

Cytobank can help with data management and sharing, in addition to data analysis. When you upload to Cytobank, the data are securely backed up in case of a personal computer failure and are available to be shared with colleagues or collaborators. Also, the annotation features in Cytobank enables descriptive information for the experiment to be saved. For example, flow facility operators running sorts for users can upload the data to Cytobank, share the pre-sort and post-sort purities, and draw gates and annotate files for their users.

Do you have questions about this dataset or other tutorials? Email us at helpdesk@cytobank.org.

- Angela

Reference:

Park CY, Majeti R, Weissman IL. In vivo evaluation of human hematopoiesis through xenotransplantation of purified hematopoietic stem cells from umbilical cord blood. Nat Protoc. 2008;3(12):1932-40. PMID: 19180077

Jonathan from Cytobank/Stanford recommends what he calls “future proofing” in order to avoid this problem. He explained this approach during a CYTO 2011 Pre-Congress course in his talk titled “Flood Cytometry: Embracing Single Cell Systems Biology (and coping with large cytometry experiments).” In that talk, he outlined four easy steps that are useful for experiments of all sizes.

When collecting on the cytometer:

1. Tag your FCS files with key experiment details (e.g. “Patient-J01 IL-2 15m”)
2. Label the channels you are measuring (before collecting data)
3. Make sure scales and compensations work (before collecting data)
4. Encode clinical sample IDs (don’t use HIPAA sensitive information)

Click the image to download as a PPT slide

You’ll notice right away that these things are “obvious” – you know that you should be following these steps, but maybe you feel like you don’t really have the time. In fact, you don’t have the time NOT to do these steps! Spending a few minutes doing these things at the start of your experiment will save you hours during analysis and protect your data from oblivion.

The annotation process in Cytobank is designed to take advantage of any information you entered during sample collection. The more information you enter during collection, the easier and faster your analysis in Cytobank becomes (watch this video to see an example of annotating the Conditions figure dimension). Not only do annotations help you build and arrange your plots in Cytobank, they are also there to help you or your collaborator identify which FCS file corresponds with which experimental sample.

The main rule for tagging your FCS files during sample collection is to include the information that makes that sample unique within that particular experiment. You want to avoid maintaining a parallel “key” in your lab notebook that explains what your FCS files are. There is often some pressure to collect your files quickly while on the cytometer and thus, you may end up not filling in a unique tag for each file. The concern is not that you will lose the key (which of course would be really bad), but instead that having to correlate the files with the key creates several issues:

1. It’s boring and slow, which creates a barrier to re-using that data later
2. There may be mistakes in deciphering the key and files if it’s being done by a person, especially if it’s not the person who originally collected the samples
3. You lose the opportunity to search your files in Cytobank according to experimental variables (e.g. “show me all the experiments where I studied Patient-J01” or “where I stimulated with IL-2” or “where I measured p-STAT5”)
4. Neither you nor you collaborators are able tell “at a glance” what the experiment was about

Experiment variables are often things like timepoints, stimulation conditions, dosages, what you measured on each channel, and codes for individual patients. In the example above, the file or sample name is “Patient-J01 IL-2 15m”, which might mean that the cells in that file were from Patient J01 and were treated with IL-2 for 15 minutes as part of the experiment.

We recommend the labeling strategy below. The instructions are tailored to BD’s FACSDiva software but are generally applicable to any other data acquisition software for cytometers.

Specimen (or tube) labels

Label each specimen and tube with text indicating how it is unique within the experiment. You might include one or more of the following:

• Sample type: Samples can include major classifications of the samples tested (e.g., wild-type vs. knock-out, tumor vs. normal, cell lines vs. whole blood, spleen, or lymph node).
• Condition: Conditions can represent stimuli or inhibitors used in the experiment (e.g., IL-2, IL-6, PMA, inhibitor14, drug35), or alternatively, growth mediums or cell state (e.g., fresh cells, frozen cells).
• Timepoint: Timepoints are specified durations used in the experiment. For example, in a phospho-flow experiment, these can represent times that samples were allowed to signal before being fixed (e.g., 30 s, 5 min, 4 h).
• Dosages: Dosage titrations are various concentrations of a stimulus or inhibitor used in the experiment (e.g., 0.1 ng/mL, 10 ng/mL).
• Individual: Individuals can be different donors or animals (e.g., donor3, BALB/c5).

Examples:

• 2min IFNa 003
• s2 lp-j110_panel 8 cd3 cd127 cd25_singlets
• 01 healthy whole blood donor1 IL-2 10 ng-mL 15 min
• Patient-J01_AtDiag_Panel1

Parameter (or channel) labels

Label each channel with the name of the thing you are measuring, which is often an antibody specificity. For phospho-flow experiments, the phospho-protein should be specifically identified, and it can be useful to indicate the amino acid residue whose state you are probing.

In addition, indicate in the channel name the way you are measuring that channel. For fluorescence flow cytometry, this is usually a fluorophore.

Examples:

• CD3-PerCP-Cy5.5
• CD4-PacBlue
• CD10-Gd156
• p-STAT5-Ax488
• p-p53-S15-Ax647
• Foxp3-EGFP

Compensating at the machine

If you compensate at the machine, Cytobank will see a “file-internal compensation” that you can use. If you want, Cytobank can extract this and save it as an editable software compensation, so you can always tweak it later. (Watch our video tutorial on modifying file-internal compensation.)

Codes for clinical samples

For clinical work, we recommend users create a coding system for human patients so that 1) they never put private patient information into flow cytometry files and 2) they have an easy to read identifier for patients that can be used in figures, slides, and papers.

Getting your labels into Cytobank

After exporting your FCS files from your acquisition software (see our blog posts on exporting from Diva and working with Accuri data), the details that you entered will be included in the name of the FCS file or included within the FCS file itself. When these files are uploaded to Cytobank, the specimen/tube names and parameter labels should be imported into Cytobank and can be used to annotate your files. If they are not, please let us know and we can work with you to see if there’s a way to transfer those tags into Cytobank!

Watch these videos to see how to annotate the Channels dimension or how to annotate other dimensions such as Conditions. The interface for Conditions and similar Figure Dimensions has been slightly updated from the one you see in the videos, but functions in a similar manner.

- Stephanie

A Cytobank project enables you to share multiple experiments with the same group of people. A project also allows you to set project-wide permission levels that let you determine whether or not people can make new illustrations and whether or not they can clone the experiments contained within the project.

For example, let’s say Bob and Joe are in the same lab and both studying leukemia. They often collect flow cytometry data that they want to share with each other. In Cytobank, Bob can create a project called “leukemia project” and make himself and Joe managers of that project. When creating a new experiment on Cytobank, Bob can specify that the experiment is part of the “leukemia project”, and Joe will automatically get access to that experiment. Since they are both managers, Bob or Joe can decide to add new members (e.g. Sue) to their project and decide what level of access this new member has.

One important change in the latest version of Cytobank (2.4.3) is that project managers are now granted full access to all experiments in the project. This change is not retroactive – any project updates that occurred before the 2.4.3 release (July 22-25, 2011) will NOT result in managers having full access to experiments in projects, unless they were explicitly granted full access.

Managers, as their name implies, manage the project. They can change project sharing/cloning settings, as well as add/delete other managers, leaders, and members to a project.

Leaders and members can view the experiments in a project (the level of access is set by the managers) and can add new experiments to a project. Leaders are no different from members, aside from the fact that they’re called leaders. An example of a project leader might be your advisor, who doesn’t need/want to manage the project but would like to stay up-to-date on new experiments.

The level of access for project members can be set as follows:

• Enable/disable making of new illustrations. Managers can decide whether to allow members to make their own illustrations with the data or to allow members just to view the saved illustrations.
• Enable/disable cloning of an experiment. Managers can also decide to enable cloning files only, cloning files and illustrations, or to disable cloning entirely.

When thinking about cloning permissions, it’s important to keep in mind that if you grant a member the ability to clone an experiment, that person can make their clone (and thus the data) public.

For more information on projects, read our documentation article titled What are projects? For a step-by-step guide for how to create a project, read the article titled Share experiments using projects or watch the short video clip below.

- Stephanie

If you’ve logged into Cytobank recently, you will have noticed some changes with the Figure Dimension interface. We’re excited about these changes, which we think will make building your plots even faster and easier than before. We briefly discussed these changes in last month’s release notes and elaborate on them in this blog post.

What do you think of the new interface? Please let us know in the comments below or email us at helpdesk@cytobank.org.

One of the first things we improved was the drag and drop motion of the Figure Dimension boxes (such as Channels, Populations, Conditions, etc.). In the new interface, rearranging Figure Dimensions is much smoother. The Dimension boxes now have grip handles to indicate that the box can be dragged and dropped. When you start to drag the box, a gray box with a dotted outline indicates where the box will drop.

We also increased the width of each box and enabled wrap-around on the label names. This is especially useful with long label names (such as Channel names) which would get cut-off in the old interface.

In the new interface, each Dimension box now has two links:

1. “Choose” is a new feature that enables you to more easily select which annotated files you want to display in your Working Illustration.
2. “Setup” is what we used to call “Edit”. (And as before, the Populations Dimension has a link for “Gate”.)

Choose

In the old interface, you would shift-click to select multiple files, something that became unwieldy when there was more than one “page” of items to select. Now, instead of scrolling within the small Dimension box, an expanded interface allows you to easily select and rearrange the labels in each Dimension. Clicking “Choose” brings up a lightbox that displays all the labels for that Dimension. Checkboxes, filter words, and Select All or None options facilitate selecting multiple labels.

Changing the order of the labels within a Figure Dimension will now rearrange the layout of your plots in your Working Illustration. The grip handle on the righthand side of each label facilitates dragging to rearrange the labels in a desired order. (The Layout Placeholders view still works for rearranging layout.)

Setup

Clicking “Setup” is equivalent to clicking “Edit” in the old interface.

For Channels, “Setup” will bring you to the same page as before, where you can assign your FCS files to different staining panels and edit the names of your reagents. For other Figure Dimensions, “Setup” will bring you to the Annotation page, where you can add labels and assign those labels to your FCS files. This page underwent some small changes recently, as detailed in our release notes for Cytobank 2.3.4.1.

The Populations Figure Dimension contains a link for “Gate” instead of “Setup”. Clicking “Gate” in Populations opens the gating applet, where you can draw gates and define populations.

Watch a short video demonstrating the new Figure Dimensions interface.

Please bear with us as we work to update all of our documentation and video tutorials. If you have any questions about how to navigate the new Figure Dimension interface, you can always reach us at helpdesk@cytobank.org.

- The Cytobank Team

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!

The Inspector window in Diva is where you name files. Click on the Tube tab, and enter sample information into this field. Before you collect your first sample, take a moment to think ahead about which Figure Dimensions on Cytobank you will use. For example, you may want to enter a donor/individual number, a timepoint label, and a stimulation condition. If you then enable and define these Figure Dimensions, Cytobank will automatically sort your files into the appropriate annotation tags.

Annotate Flow Cytometry Files in Diva (Figure courtesy of J. Irish, CYTO 2011)

When you label fluorescence channels with reagent information in Diva, Cytobank automatically pulls this reagent info from the files, further facilitating your analysis and generation of well-labeled figures. To enter reagent information in Diva, click the Labels tag in the Inspector and type in the reagent names.

Once you are done collecting data from your samples, it is time to export the data as FCS files. To preserve the names you have assigned to your files, it is important that you export your files from Diva as FCS files and NOT as experiments. Exporting an experiment from Diva will generate FCS files with numbered filenames. We are working on a way to import Diva experiments into Cytobank (and convert the numbered filenames), but until then, exporting your files as FCS files is the easiest way to import files from Diva and work with them in Cytobank.

Exporting FCS Files (from BD FACSDiva v6 manual)

Select the experiments or tubes to export, then click File → Export → FCS files. Choose a file destination, and click Save. Your files are now ready for upload and analysis on Cytobank!

- Angela

July 25-29, 2011
UC Davis Short Course in Flow Cytometry

This flow cytometry course will take place in the Genome Center and Tupper Hall of the UC Davis campus in Davis, CA and is co-sponsored by FloCyte. On Thursday July 28th, Nikesh will be giving a talk in the morning and leading a Cytobank lab in the afternoon. You can register here and view the schedule here.

Nikesh Kotecha, Ph.D.
Talk: Detection of Cell Signaling Events by Flow Cytometry (July 28, 9-10 am, GBSF 1005)
Cytobank lab: participants and outsider flow people invited (July 28, 1-3 pm, GBSF 1005)

September 5-7, 2011
Flow Cytometry for Intracellular Targets – Hands on Phosphoflow Workshop

Jonathan and Nikesh will be traveling to Bergen, Norway to speak at this workshop and lead the lab and data analysis. Click here to view the flyer and schedule.

- Stephanie

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.

Cytobank collaborated closely with BD to produce the Buffer Compatibility Resource, which makes primary data from BD’s extensive antibody testing available to you. Through an interactive page listing key details of tested antibodies and fluorochromes, you can click “View” to consult a detailed datasheet (powered by Cytobank Reports) and then click again to interact with the raw data in Cytobank.

How does this help me?

Currently, the Buffer Compatibility Resource offers extensive testing data on over 50 antibodies available in BD’s catalog. BD scientists stained human and mouse primary samples, as well as various cell lines. Samples were also permeabilized with one of four buffers. Datasheets for each antibody are organized by fluorochrome and permeabilization buffer so that you can quickly assess the staining efficacy of the various conjugates in each of the buffers.

Both intracellular and surface antibodies have been tested. Thus, when designing phospho-flow experiments, the Buffer Compatibility Resource enables you to assess which reagent and buffer combination will give you optimal signal. Surface antibodies were also run at different titrations, providing you with valuable data on how to get the best staining resolution.

Finally, BD has also made available to you all of the experimental protocols that their scientists used to stain these samples and test these antibodies. Standard and alternative protocols can be accessed in the top right corner of the main Buffer Compatibility Resource page, and additional protocols are accessible through the link on the bottom of the box. Each datasheet also provides any necessary details on stimulation conditions or caveats that are specific to each reagent or sample.

A quick guide to the Buffer Compatibility Resource

The interface allows you to quickly search by keywords, filter by fluorochrome or laser, and sort search results by clicking on column headers. Clicking “View” brings you to a detailed datasheet with plots organized by fluorochomes and permeabilization buffers. Reagents for each datasheet are listed in the top right corner, along with a link to the BD catalog so you can quickly access the reagents you need.

Beneath each set of data plots, you will find a link to “View in Cytobank.” Clicking on this link will prompt you to log in to Cytobank, where you can interact with the data. You can also clone the experiment files to obtain your own copy of the data and begin gating and analyzing the data yourself.

Don’t have an account on Cytobank? Click here to register (for free).

Questions or comments? Don’t see your favorite antibody? Email us!

- The Cytobank Team

June 13-14, 2011
Toronto Flow Cytometry Research Workshops & Seminars
The SickKids-UHN Flow Cytometry Facility, Toronto, Ontario, Canada
Nikesh Kotecha, Ph.D.
Talk: Phosphoflow and Cytobank: Development and Management of Flow Cytometry Based Signaling Assays for Translational Research (June 14, 10:00am)
Hands-on training (June 14, 3:30pm)

June 16, 2011
FloCyte Phospho Flow Course
Immune Disease Institute, Harvard Medical School, Boston, MA
Nikesh Kotecha, Ph.D.
One of the instructors

June 23-24, 2011
Second Annual Southeastern Flow Cytometry Interest Group Meeting
Georgia Center for Continuing Education, Athens, GA
Nikesh Kotecha, Ph.D.
Talk: Cytobank: Manage, Share and Analyze Flow Cytometry data from Anywhere (June 24, 1:40-2:10pm, Room L)

Questions? Contact us at info@cytobank.org.

- Stephanie

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:

To give another user full access to your experiment…

Open the experiment from your Inbox, and you will be brought to the Experiment Details page. On the left side of this page, you will see a box called Sharing Permissions. Simply type in the name of the user with whom you wish to share your experiment, and click on the user’s name when it pops up. This will give the other user full access to your experiment, including the ability to download your raw data files, view the plots you have created, and clone a copy of your experiment for their own use. If you want to share an experiment with someone who hasn’t yet registered for Cytobank, click the “Invite a new user” button within the Sharing Permissions box.

To give another user limited access to your experiment…

There may be times when you want to show a colleague the plots resulting from your analysis, but you would prefer that they not change any of the settings in your experiment. To share while restricting another user’s ability to work with Illustrations or raw experiment files, make use of Cytobank Projects. You can read more about this way of Cytobank-internal sharing on our documentation site.

- Angela

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!

Configuring Plot Scales on Cytobank

After collecting your data in CFlow, export the data in the FCS format under the File menu (watch a video demonstrating this). Next, upload these FCS files to Cytobank by creating a new experiment. If your data look condensed toward the plot origin, you can easily spread them out by adjusting the Plot Scales ranges. Under Plot Scales on the Illustration page, change the FCS-A maximum value to 2,300,000 and the SSC-A maximum value to 1,000,000 if these scatter channels were collected in linear mode. From here, all annotation and analysis is accomplished as described in our tutorials.

Scatter gating (left) and CD4-PE gating (right) in Cytobank

If you have a question about whether data from your cytometer is compatible with Cytobank, send us an email! If your cytometer isn’t part of the more than 30 cytometers with which we have experience, send us a sample FCS file and we’d be happy to test it!

- Angela

Register as a user on Cytobank to be added to our mailing list. Scroll down on this page to see options for email or RSS subscriptions to our blog (bottom of the right sidebar).

What is SPADE?

SPADE (which stands for 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 above. SPADE works for data from both ‘classic’ fluorescence flow cytometry and mass cytometry.

The SPADE tree above shows CD14 expression in different cell populations in human bone marrow. To read more about SPADE, look up the mass cytometry study recently published in Science from Garry Nolan’s lab at Stanford and DVS Sciences.

- The Cytobank Team

Reference:

Bendall SC, Simonds EF, Qiu P, Amir ED, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, Nolan GP. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science. 2011 May 6; 332(6030):687-96. Abstract.

May 13-17, 2011
IMMUNOLOGY 2011
98th Annual Meeting of the American Association of Immunologists
Moscone Center, San Francisco, CA
Booth 307

May 21-25, 2011
CYTO 2011
XXVI Congress of the International Society for Advancement of Cytometry (ISAC)
Baltimore Convention Center, Baltimore, MD
Booth 322

There will be a number of talks and posters involving members of the Cytobank team at CYTO 2011. Be sure to check out the presentations listed below.

Friday, May 20

Pre-Congress Intermediate Course
Building Rainbows: The Fundamentals of Polychromatic Flow Cytometry (flyer, schedule)
Talk: Methods for Presentation and Analysis of Complex Flow Cytometry Data
Jonathan Irish
8:00am – 5:00pm

Saturday, May 21

Tutorial 5: Phospho Flow Cytometry: Single Cell Signaling Networks (Abstract #5)
Peter Krutzik
10:15am – 12:15pm, Room 339 – 340

Tuesday, May 24

Parallel Session 6: High Throughput Screening and Discovery

Automating Signaling and Cell Cycle Analysis in Drug Discovery: Determining the Effect of Chemotherapeutics on Leukemic Cells (Abstract #78)
Tiffany Chen, Matthew Clutter, Nikesh Kotecha, Garry Nolan, and Serafim Batzoglou
8:15 – 8:30am, Room 341 – 342

Wednesday, May 25

Parallel Session 7: Cell Proliferation and Death/Cytometry Informatics

Inference of Context-Specific Pathways in Ovarian Cancer from High-Dimensional Mass-Cytometry Data (Abstract #97)
Robert Bruggner, Bernd Bodenmiller, Nikesh Kotecha, David Dill, and Garry Nolan
8:30 – 8:45 am, Room 337 – 338

Algorithmically Recovering the Hematopoietic Lineage from High-Dimensional Cytometry Data Using SPADE (Abstract #99)
Michael Linderman, Erin Simonds, Peng Qiu, Zach Bjornsen, Nikesh Kotecha, Teresa Meng, Sylvia Plevritis, and Garry Nolan
9:00 – 9:15am, Room 337 – 338

Posters

FlowSite – A Public MIFlowCyt Compliant Data Repository
Poster B52 / Abstract #180
Karin Breuer, Josef Spidlen, Chad Rosenberg, Nikesh Kotecha, Garry Nolan, and Ryan Brinkman

Optimization Requirements for Multiplexed Intracellular and Cell Surface Protein Staining for Flow Cytometry
Poster B189 / Abstract #317
Erika O’Donnell, Guo-jian Gao, Christopher Coveney, Xiao Wang, Xiao-Wei Wu, Ai-Li Wei, Xiang Dong Ji, Lori Anderson, Nikesh Kotecha, and Jurg Rohrer

Questions? Email us at info@cytobank.org. We look forward to seeing some of you at IMMUNOLOGY 2011 or CYTO 2011!

- Stephanie

Also, more details to come, but stay tuned for a new resource from BD Biosciences powered by Cytobank Reports. (If you’re attending IMMUNOLOGY 2011 or CYTO 2011 this month, stop by our booth to preview this resource!)

In developing Cytobank Reports, we are moving towards realizing one of our key goals: effective communication of flow cytometry results. Figures in a journal article represent only one end of the information spectrum. Though easy to read, static figures fail to capture details of analysis and lack the depth of information necessary for true transparency and openness, particularly in a field like flow cytometry.

The new functionality on Cytobank enables us to create a customizable Report that not only includes plots and descriptions but also links to Saved Illustrations in Cytobank, gating hierarchy for the experiments shown, and sections for abstracts, protocols, and other pertinent details. From the Report, readers can log into Cytobank to view and interact with the data.

Why We Need Reports

With its sharing features, Cytobank helped to fill a key NIH mandate for making published data and results available to the scientific community. Cytobank Reports builds on this by providing a public interface from which to view analyzed data and to access the raw data. Cytobank Reports will work together with existing flow cytometry data standards, including MIFlowCyt (Minimum Information about a Flow Cytometry Experiment) and ACS (Analytical Cytometry Standard). (Learn more about these data standards here.)

Quick dissemination of data and findings is one important reason for Cytobank Reports. The rapid pace of research compared with the relatively slow turn-around time on peer-review and publication sometimes results in a disconnect between the most recent findings from the lab and published articles. Cytobank Reports can provide flow cytometry researchers with a medium in which they can quickly pull together plots and other information from experiments stored on Cytobank and assemble a Report to share exciting new findings with their colleagues.

The mass cytometry study (read our take on it here) demonstrates other reasons why a resource like Cytobank Reports is necessary. Both the size of the dataset (3.3GB) and the complexity of analysis preclude the utility of simple file-sharing to adequately make available all of the information necessary for understanding the details of the analyses and for deeper mining of the rich data set. With Cytobank Reports, plots and information can be organized neatly (much as they are in a journal article) and include links to directly access the analysis and the online data stored in Cytobank.

View the first Cytobank Report by going to the Nolan Lab’s Public Cytometry Collection and clicking on the “View Data” link. Anyone can view the Report, but, in order to access the data and analysis in Cytobank, an account on Cytobank is required (register for free).

Report functionality will be made available to users in the near future. In the meantime, we’d love to hear your questions, comments, and suggestions.

- The Cytobank Team

References:

Bendall SC, Simonds EF, Qiu P, Amir ED, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, Nolan GP. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science. 2011 May 6; 332(6030):687-96. Abstract.

Spidlen J, Shooshtari P, Kollmann TR, Brinkman RR. Flow cytometry data standards. BMC Res Notes. 2011 Mar 7;4:50. PMID: 21385382 Open Access Article