CANTAO: GUIDING CLUSTERING AND ANNOTATION IN SINGLE-CELL RNA SEQUENCING USING AVERAGE OVERLAP

ABSTRACT: Single-cell RNA sequencing allows defining cellular identities based on transcriptional similarity using unsupervised clustering. However, a single clustering resolution may not yield groups of cells that represent both broad, well-defined populations and smaller subpopulations simultaneously. Therefore, when cell identities are not known prior to sequencing, robust comparison and annotation of inferred de novo clusters remains a challenge. Here, we introduce CANTAO, in which we propose the average overlap metric to define the distance between single-cell clusters by comparing ranked lists of differentially expressed genes in a top-weighted manner. We benchmark CANTAO in truth-known datasets comprised of similar yet distinct cell populations and show that evaluating clusters with average o

SUBMITTER: Christopher Thai 

PROVIDER: S-SCDT-10_1038-S44320-025-00176-4 | biostudies-other |

REPOSITORIES: biostudies-other