CyCadas: accelerating interactive annotation and analysis of clustered cytometry data.

ABSTRACT:

Motivation

Single cell profiling by cytometry has emerged as a key technology in biology, immunology and clinical-translational medicine. The correct annotation, which refers to the identification of clusters as specific cell populations based on their marker expression, of clustered high-dimensional cytometry data, is a critical step of the analysis. Its accuracy determines the correct interpretation of the biological data. Despite the progress in various clustering algorithms, the annotation of clustered data still remains a manual, time consuming and error-prone task. We developed a user-friendly cluster annotation and differential abundance detection tool that can be applied on data generated with Self Organizing Map clustering algorithms, thus simplifying the annotation proces

SUBMITTER: Hunewald O 

PROVIDER: S-EPMC11488975 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature