Are your flow cytometry analyses being hampered by laborious manual gating and the vast output of highly complex data?
The time it takes from acquisition of cytometry data to making actionable decisions is a long and manual process. This impacts the efficiency and quality of your science. Our flow cytometry analysis solution – the CytoML Suite – helps users automatically gate their flow cytometry data with semi-automated gating and fully unbiased approaches, saving up to 80% of scientists’ hands-on time.
Key benefits of Aigenpulse’s flow cytometry analysis solution:
Increase throughput of your flow cytometry data processing and analytics by as much as 600%.
Free up to 80% of scientists’ hands-on time.
Automate end-to-end process for large numbers of raw files by leveraging workspace templating and machine learning to empower cytometry processing and analytics.
No coding/machine learning experience necessary!
The single point of entry for all cytometry data makes the organisation of results simpler.
Insights can easily be derived from exploring the data in different planes using the in-built plotting tools.
Simultaneously increase accuracy, reproducibility and quality of flow cytometry data processing and analytics.
High level of accuracy (equivalent to and surpassing that of manual gating) can be achieved.
Automated gating with CytoML is more robust to variation than manual gating.
Retain all algorithm parameters for fully transparent and reproducible cytometry gating.
Leverage machine learning to scale-up and automate gating using unsupervised and guided population identification – all built-in to the Aigenpulse CytoML Suite.
Streamline cytometry data processing and QC
Parse, integrate and standardise all popular flow cytometry data formats into the system using one seamless process.
Import data using an easy-to-use web interface.
Quality assessment reporting on data quality using FlowAI and FlowClean can be generated, providing full visibility on data quality.
Fully federated and audit logging for processing and integration parameters, enabling re-use and enhancing efficiency.
Enable GxP validation
All CytoML processes align to GxP/GAMP5 guidelines, are ISO27001 and ISO 9001 certified, and meet US – 21 CFR Part 11 and EudraLex – Volume 4 – GMP – Annex 11 regulations.
Every analysis, every dataset, every parameter, every report generated in the Aigenpulse CytoML Suite is retrievable and reproducible with timestamps, user information, parameters used and data input and output.
The latest release of the Cyto-ML Suite (v5.2) introduces new unbiased analysis features and guided/semi-automated analysis, providing 100% reproducibility for researchers who need data to support regulatory use cases.
No coding interface enables you to leverage supervised machine learning algorithms to recapitulate your manual gating automatically.
Reduce bias with a range of high performing algorithms built on uni/bi-modal density-based evaluation techniques, which assesses each file individually.
Identify large, small and transitionary populations with ease using built-in utility gates.
Automate your analysis on many files by creating workspace templates which join many individual gating steps into reproducible, scalable, automated workflows.
Beneficial for exploratory use cases, including FlowSOM and Phenograph for algorithm-based clustering.
Powerful dimensionality reduction methods such as tSNE and UMAP to visualise connected data.
Batch processing tool means a range of parameters can be simultaneously explored to assist scientists in finding the best representation of their data.
Once interesting clusters have been identified, these can be overlaid with marker expression and many types of meta-data to drive hypothesis testing.
Streamlines the process of assigning identities to populations from clustering outputs – a traditionally arduous task.