FlowCT for the analysis of large immunophenotypic data sets and biomarker discovery in cancer immunology.

ABSTRACT: Large-scale immune monitoring is becoming routinely used in clinical trials to identify determinants of treatment responsiveness, particularly to immunotherapies. Flow cytometry remains one of the most versatile and high throughput approaches for single-cell analysis; however, manual interpretation of multidimensional data poses a challenge when attempting to capture full cellular diversity and provide reproducible results. We present FlowCT, a semi-automated workspace empowered to analyze large data sets. It includes pre-processing, normalization, multiple dimensionality reduction techniques, automated clustering, and predictive modeling tools. As a proof of concept, we used FlowCT to compare the T-cell compartment in bone marrow (BM) with peripheral blood (PB) from patients with smolderi

SUBMITTER: Botta C 

PROVIDER: S-EPMC8791585 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature