Kaluza C Analysis Software

Purpose-built for clinical laboratories, Kaluza C Flow Cytometry Analysis Software helps you turn critical data into meaningful patient reports.

With the power to processes multicolor files of up to 20 million events in real time, Kaluza C software streamlines quality control (QC) reporting requirements and enables you to analyze any flow cytometry standard (FCS) compliant file.

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Features

Listed with the FDA as a medical device
Seamless integration with laboratory information systems (LIS)
Powerful, real-time processing
Compliant with FCS standard 3.1 or earlier

Medical Device

Kaluza C software is listed with the FDA as a medical device and is also a CE-marked IVD product, ultimately helping to reduce your tool validation work.

Comprehensive Compatibility

Compatible with listmode data files that are compliant with FCS standard 3.1 or earlier all from all acquisition software packages and cytometers.

Enhanced LIS Integration

Kaluza C software provides integration with the LIS, which reduces the need for manual data entry and manual transcription.

Content and Resources

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Kaluza C Analysis Software Brochure Kaluza C Analysis Software streamlines clinical QC reporting requirements and addresses flow cytometry standardization issues

Using Standardized Dry Antibody Panels for Flow Cytometry in the Assessment of Altered Immune Profiles in Response to SARS-CoV2 Infection In order to identify early indicators of disease severity in SARS-CoV2-infection, the proportions of well-established immune cell phenotypes have been subject to extensive research, utilizing flow cytometry as a core technology1-3. In order to ensure comparable and consistent results in the massively multi-institutional research setting of a global pandemic, the use of standardized antibody panels and procedures, as demonstrated by The ONE Study4-6, is a promising approach that also can lower technical barriers

Offline Flow Cytometry Analysis Software: Importance of Scaling and Data Visualization This whitepaper discussed the flow cytometry open platform data structure and how it facilitates for robust offline analysis, the importance of data scaling and display features in ensuring your data looks consistent with the native environment, and illustrates specific examples comparing the native display to an offline data analysis software across a variety of platforms and manufacturers.