5 costly aspects of manual data analysis in flow cytometry and how the Cytobank platform can help
Multiple timepoints, multiple individuals, multiple sites, and multiple populations of interest. The amount of data research flow cytometry studies generate continues to grow. And with the dimensionality of datasets having increased from traditional 4-5 color low parameter to 10-20 or more colors, researchers around the world are looking for ways to move from raw data to visualization and evaluation more efficiently, and avoid the costly aspects associated with manual data analysis. Here are five of those costly aspects and how the Cytobank platform can help.
1. Data Rework
Costly aspect
Manually gating separate cells into discrete populations is highly subjective, and can often be completed properly only by experienced researchers. And missing insights and drawing speculatory conclusions on subjective results can lead to you having to rework and revise your work.
Cytobank solution: an unbiased analysis approach
This can help you discover patterns and peculiarities that just can’t be found with conventional, manual methods and help you realize the full potential of your valuable data.
2. Wasted time
Costly aspect
Installing plugins for data analysis. Moving huge datasets across devices. Trying to figure out ways to efficiently organize raw data and analytical results from different projects. It’s tasks like these that take up a lot of your precious time—time that would be better spent interpreting results and delivering insights.
Cytobank solution: streamlined machine learning-assisted analysis
As a continuously updated cloud-based application, validated version releases are pushed automatically and—unlike some conventional methods—there’s no need for you to reinstall or reconfigure any software on the computers in your lab.
3. Multiple software applications
Costly aspect
Manually transferring data files between multiple software tools and applications can create yet another error-prone step in your data analysis workflow.
In addition, learning several different software applications and managing multiple licenses and user accounts can be both tedious and overwhelming.
Cytobank solution: a single software solution for data analysis, visualization, statistics, storage, backup and traceability
Analyses are conducted in the cloud using a web-enabled device and includes the use of integrated algorithms—no coding or R scripting required. The platform’s clustering, dimensionality reduction, automatic gating and visualization tools leverage the scalable compute and collaborative power of the cloud for large analyses to be done quickly.
4. Data sharing
Costly aspect
Processing single-cell data creates a lot of data points and large files. The sheer size of these files can make data sharing complicated and cumbersome.
An added layer of complexity is how difficult it can be for colleagues to interpret analyzed files. Not being able to see the analysis steps that were taken could result in subjective and inaccurate conclusions.
Cytobank solution: comprehensive data analysis can be shared and viewed with a few clicks, from web-enabled devices
You can drill down from a publication-quality figure to the underlying primary data, ensuring that important knowledge on how scientific conclusions were drawn is retained, securely stored and documented.
5. Repetitive tasks
Costly aspect
Continually repeating manual, monotonous tasks—such as gating, adjusting scales and building illustrations—pulls you away from the things you enjoy doing in the lab and makes it more difficult for you to focus on generating novel insights.
Cytobank solution: reproducible and automated data analysis
Built-in templates make manual, monotonous tasks a thing of the past, and the automatic gating feature reduces variability and time spent on tedious manual analysis. With it you can complete gating in less than one minute and easily share models with other users.
For Research Use Only. Not for use in diagnostic procedures.
