Recent advances in single-cell technologies have enabled the characterization of epigenomic heterogeneity at the cellular level. Computational methods for automatic cell type annotation are urgently needed given the exponential growth in the number of cells. In particular, annotation of single-cell chromati...
Within this set of cell types, we suspect that the observation of platelets as a majority cell type, rather than megakaryocytes2, likely reflects annotation differences in reference data. We observed distinct transcriptional contributions from solid tissue-specific cell types from the intestine, liver...
Cell type identification of the COVID-19 dataset was done according to the authors’ annotation (“cell_type_fine” identity class) and clusters were annotated based on the identity of the majority of the cells in the cluster. When several clusters with the same cell type were identified, a...
For deconvolution and cell type annotation, single-cell RNA sequencing and ST data were integrated via the 'CARD' (v 1.1) [27] package with default settings. Initially, a 'CARD' object was created with the CreateCARDObject function, and the results were computed using CARD_deconvolution with ...
For cell annotation of each cell type, we utilized published literature gene expression signatures and manual review of differential genes among clusters [25, 26, 47, 51, 58, 95]. Additionally, we again utilized SingleR (v0.99.10) and BioTuring for unbiased cell annotation. We utilized t-SNE...
First, the expression matrices in raw_UMI_count format were uploaded to ASAP along with their annotation files. The annotation file contains information on the class (normal or tumor), type (epithelial, mast cell, etc.), and subtype of each cell. Then cell filtering was done. Cells with ...
The complete annotation dataset for biological process, molecular function, and cellular component GO terms was used for analysis. CRISPR-Cas9 and overexpression analysis for candidate genes related to cotton plant regeneration Three genes identified from the scRNA-seq and regulatory network relates to ...
Therefore, to further assess whether the marker genes were sufficient to serve as a classifier for cell identity, the AUC values of highly expressed marker genes were calculated and assisted in cell type annotation (see Material and methods). We created integrated pipelines of scRNA-seq in cattle...
Cell type annotation Our cell type annotation is based on the imputed gene activity of known liver cell marker genes from CellAtlas75. To calculate the imputed gene activities, fragments mapping to gene bodies or promoter regions of genes (up to 2 kb upstream of a gene) were summed up us...
Cell type annotation Cell types in all datasets were manually annotated as described in ref. 48, and cross-referenced with annotations present in the single-cell database PanglaoDB107. Identification of major clusters was performed with the FindClusters() algorithm in the Seurat package, which uses...