Automated identification of stratifying signatures in cellular subpopulations.

ABSTRACT: Elucidation and examination of cellular subpopulations that display condition-specific behavior can play a critical contributory role in understanding disease mechanism, as well as provide a focal point for development of diagnostic criteria linking such a mechanism to clinical prognosis. Despite recent advancements in single-cell measurement technologies, the identification of relevant cell subsets through manual efforts remains standard practice. As new technologies such as mass cytometry increase the parameterization of single-cell measurements, the scalability and subjectivity inherent in manual analyses slows both analysis and progress. We therefore developed Citrus (cluster identification, characterization, and regression), a data-driven approach for the identification of stratifying

SUBMITTER: Bruggner RV 

PROVIDER: S-EPMC4084463 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature