… of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing
single-cell RNA sequencing data, yet manual annotation is time-consuming and partially …

… In this study, we develop and establish TOSICA, a Transformer-based cell type annotation
… cell type annotations under many scenarios, including but not limited to new cell type …

… ten cell type annotation methods publicly available as R packages. Eight of them are popular
methods developed specifically for single-cell … among cell types, and increased cell type …

… an excellent and unbiased performance on cell type annotation with a desirable precision. …
five annotated cell types (monocytes cells, T cells, NK cells, megakaryocytes cells, and B cells)…

… model, single-cell bidirectional encoder representations from … then transferred to the cell type
annotation task of unseen and … of scBERT on cell type annotation, novel cell type discovery, …

… between real cell type labels and cell types annotated by EpiAnno (… annotated 96.2% of
EX, MG, AC and OC cells, but annotated some IN cells as EX cells because these two cell types …

… of cells in a single assay based on transcriptome profiling. In most analysis protocols, single-cell
type annotation … Still, the accurate cell-type annotation for single-cell transcriptomic data …

… type identification is critical for mechanistic studies. In most current analysis protocols, cell
type-based cluster annotation … , resulting in poor replicability of cell type annotation. This study …

… Using the cell type annotations from the single-cell data, we trained a DNN to classify cell
types. As expected, our classifier derived a cell type mapping agreeing with known spatial …

… be used for cell annotation, ie to predict cell-type labels from single-cell gene expression …
Thus, cell-type prediction based on gene-signature derived cell-type labels is potentially too …