Ontology highlight
ABSTRACT:
SUBMITTER: Leelatian N
PROVIDER: S-EPMC7340505 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
Leelatian Nalin N Sinnaeve Justine J Mistry Akshitkumar M AM Barone Sierra M SM Brockman Asa A AA Diggins Kirsten E KE Greenplate Allison R AR Weaver Kyle D KD Thompson Reid C RC Chambless Lola B LB Mobley Bret C BC Ihrie Rebecca A RA Irish Jonathan M JM
eLife 20200623
A goal of cancer research is to reveal cell subsets linked to continuous clinical outcomes to generate new therapeutic and biomarker hypotheses. We introduce a machine learning algorithm, Risk Assessment Population IDentification (RAPID), that is unsupervised and automated, identifies phenotypically distinct cell populations, and determines whether these populations stratify patient survival. With a pilot mass cytometry dataset of 2 million cells from 28 glioblastomas, RAPID identified tumor cel ...[more]