OnClass’ ability to annotate cells with any cell type in the Cell Ontology motivates us to examine whether we could improve cell type annotation on large and diverse collections of scRNA-seq datasets. Improved unseen cell type annotations within the same dataset To investigate how well OnClass ...
Cell type annotation labels, batch labels and clustering labels are projected onto the visualizations. Source data are provided as a Source Data file. Full size image Secondly, with the accumulation of public scCAS data, datasets from different sources, tissues, donors, or batches pose great ...
Census: accurate, automated, deep, fast, and hierarchical scRNA-seq cell-type annotation. BioRxiv. About Accurate, deep, fast, and fully-automated scRNA-seq cell-type annotation Resources Readme Activity Stars 10 stars Watchers 1 watching Forks 3 forks Report repository Releases No ...
We chose to use the annotation from a study that identified mesenchymal cell types based on scRNA-seq and immunofluorescence, and in which the identified populations strongly overlap with ours (Tsukui et al.)28. The adventitial fibroblasts of Tsukui et al. 28 (Dcn+ Ly6a+) resemble the mesench...
CellTypist is an automated cell type annotation tool for scRNA-seq datasets on the basis of logistic regression classifiers optimised by the stochastic gradient descent algorithm. CellTypist allows for cell prediction using either built-in (with a current focus on immune sub-populations) or custom ...
immune cell clustering and annotation, integrating seven reference-based and four marker gene-based computational methods, supported by manually curated marker gene sets [168]. Comparative studies have shown that ImmCluster provides more accurate and stable cell type annotation than individual methods [...
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 ...
In addition, we used the human GO_Biological_Process_2021 library to execute Enrichr [22] on DEGs with log2 fold change above 2 and p-value and adjusted p-value both below 0.01. For cell-type annotation, we used the expression of all genes and calculated the mean expression of its ...
Annotating cell types on the basis of single-cell RNA-seq data is a prerequisite for research on disease progress and tumour microenvironments. Here we show that existing annotation methods typically suffer from a lack of curated marker gene lists, impro
Cell annotation with k-NN label transfer We label RNA mixtures using k-NN based on the labels of the neighboring cells in the single cell atlas the mixture was projected into. Zonated gene expression scoring For each gene, we compute the distance from an idealized zone-specific measurement as...