In this paper, we describe a single-cell RNA sequencing (scRNA-seq) dataset that defines vascular and vessel-associated cell types and subtypes in mouse brain and lung. The dataset contains 3,436 single cell transcriptomes from mouse brain, which formed 15 distinct clusters corresponding to cell...
Single-cell RNA-seq is an unbiased approach that has extended our understanding of heterogeneous tissues, including mouse and human embryonic gonads.18,19,20We reasoned that analysis of stage-specific gene expression profiles of individual spermatogenic cells could provide unbiased and novel insights int...
Single-cell RNA sequencing (scRNA-seq) has revolutionized our ability to characterize individual cells in depth (Kolodziejczyk et al., 2015); it was recently utilized in the intestine to identify cell types (Grün et al., 2015) and sub-populations of intestinal stem cells (Yan et al., ...
And then the cellular atlas of RILI liver was generated by profiling 9,641 cells isolated from X-ray irradiated mice livers and control ones from RILI mice model using single-cell RNA sequencing (scRNA-seq). Seven cell types were identified, including B cells, natural killer cells, T ...
Single cell RNA-sequencing (scRNASeq) has advanced our understanding of lung biology, but utility is limited by the need for fresh samples, loss of cell types by death or inadequate dissociation, and transcriptional stress responses induced during tissue digestion. Single nucleus RNASeq (snRNASeq)...
Using single-cell RNA-sequencing, we show that peripheral nerve injury induces the generation of a male-specific inflammatory microglia subtype, and demonstrate increased proliferation of microglia in male as compared to female mice. We also show time- and sex-specific transcriptional changes in ...
As of June 18, 2021, we have evaluated 16,983 mouse microarray or RNA-seq data sets (including bulk and single-cell RNA-seq data), identified 3199 data sets as relevant for GXD, and completed the metadata annotation for 3188 data sets. The searchable index is available via the RNA-Seq ...
2.3. Single cell RNA-seq data analysis We preprocessed the scRNA-seq reads using the 10× GENOMICS Cell Ranger pipeline. In general, we aligned the reads to the mouse genome (mm10) with the setting “--r1-length=26 --r2-length=98.” We applied other default cell ranger parameters to ...
We used single-cell RNA sequencing (scRNA-seq) of 12,423 cells from healthy human bladder tissue samples taken from patients with bladder cancer and 12,884 cells from mouse bladders to classify bladder cell types and their underlying functions. We created a single-cell transcriptomic map of ...
In this study, we used single-cell RNA-sequencing (scRNAseq) to define the molecular logic by which SGN subtypes diversify in the mouse. Our detailed analysis of transcriptional dynamics of SGNs from several embryonic and perinatal stages indicates that neuronal subtypes successively emerge during HC...