Health AI Central
Peer-Reviewed Publication
Brief Bioinform2026;27(5)September 1, 2026Journal Article

scDiagnostics: systematic assessment of cell type annotation in single-cell transcriptomics data.

Anthony Christidis1, Andrew Ghazi1, Smriti Chawla1, Nitesh Turaga1,2, Robert Gentleman3, Ludwig Geistlinger1
1Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA 02155, United States.
2Translational Research Division, Tempus Labs, 600 West Chicago Avenue, Chicago, IL 60654, United States.
3Department of Data Science, Dana Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215-5450, United States.
PubMed DOI

Abstract

Although cell type annotation has become an integral part of single-cell analysis workflows, the assessment of computational annotations remains challenging. Many annotation tools transfer labels from an annotated reference dataset to a new query dataset of interest, but blindly transferring labels from one dataset to another has its own set of challenges. Often enough there is no perfect alignmen…

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