Here, using single-cell analysis of human peripheral blood mononuclear cells (PBMCs) exposed to short term (25 hours) simulated microgravity, we characterize altered genes and pathways at basal and stimulated states with a Toll-like Receptor-7/8 agonist. We validate single-cell analysis by ...
This dependence can introduce variability, particularly when analyzing complex or highly variable biological samples, or complicate measurement due to the complex and variable nature of reference production, especially for protein interaction quantitative references or protein conformation references. Platforms ...
Singlets were identified on the basis of feature-barcode counts, and cells with multiple barcodes were removed, resulting in 20,678 cells for analysis. Normalization, PCA, clustering and UMAP were performed on the top 2,000 highly variable genes. Flow cytometry Cells were dissociated using ...
term persistence of CAR-T cells (Fig.1d). The researchers performed RNA-sequencing analysis on sorted T cell subsets from all 71 patients, followed by paired CITE-seq and scATAC-seq on T cells from six of these patients. The chronic interferon signaling regulated by interferon regulator factor ...
‘NP’ (non-perturbed). In contrast, PS models perturbation responses as a continuous variable ranging from 0 to 1, allowing users to specify gene lists as perturbation signature genes. This provides a more flexible framework for analysing perturbation responses, including in a cell-type-specific ...
Clear cell renal carcinoma (ccRCC) is a heterogeneous disease with a variable post-surgical course. To assemble a comprehensive ccRCC tumor microenvironment (TME) atlas, we performed single-cell RNA sequencing (scRNA-seq) of hematopoietic and non-hematopoietic subpopulations from tumor and tumor-adjace...
Microfluidic technology is increasingly utilized in single-cell sequencing due to its compact size, high throughput, and sensitivity (Fig.2c). It excels in the isolation, sorting, and sequencing of individual cells, facilitating efficient capture and detailed transcriptome analysis. The C1 Single-Cell...
Annotations for cell populations were grounded on both hematoxylin and eosin staining (HE) sections and the markedly variable genes within each cluster. The functions SpatialDimPlot and SpatialFeaturePlot were synergistically used to delineate the expression levels of cells within the ST data. Cell type...
4a). Our analysis revealed that the expression ratio was variable across different blood cancer cell lines, but more uniform within a single-cell line (Fig. 4a, b). HL-60 acute promyelocytic leukemia cells showed the highest expression ratio, while EJM multiple myeloma cells showed the lowest ...
expression analysis identified 5321 cluster-defining genes (Supplementary Fig.2a’), yielding five subsets of supporting cells (n = 9200 cells, clusters 0, 1, 2, 3, and 4), one putative hair cell precursor group (n = 154 cells, cluster 7), and two hair cell subtypes (n =...