Journal: NPJ Systems Biology and Applications

Article Title: Metacell-based differential expression analysis identifies cell type specific temporal gene response programs in COVID-19 patient PBMCs

doi: 10.1038/s41540-024-00364-2

Figure Lengend Snippet: a UMAP of 25,775 cells colored by cell type. b Metacell distribution across cell type space for each time point. Metacells are red while single cells are grey. c Violin plot of the number of genes detected for SEACell-generated metacells (top) compared to all single cells (bottom). d Box plots showing metacell purity for each day. The lower and upper hinges of the boxplots represent the first and third quartiles, the center line is the median, and the whiskers extend no further than 1.5 * interquartile range.

Article Snippet: Fig. 3 Summary of sMetacell output. a UMAP of 25,775 cells colored by cell type. b Metacell distribution across cell type space for each time point.

Techniques: Generated

Journal: Nature Biotechnology

Article Title: Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing

doi: 10.1038/s41587-022-01452-6

Figure Lengend Snippet: a , Number of cells assigned to each donor by Vireo. Donors were renamed to match between Ultima and Illumina. b , UMAP plots for Ultima (right) and Illumina (left) colored by donor (top) and cell type (bottom). c , Bar plots of the proportion of each Azimuth-defined cell type in each donor for Ultima and Illumina. d , Bar plots of the proportion of each Azimuth-defined T cell subtype in each donor for Ultima and Illumina. Strong agreement can be seen. e , Scatter plots of logFC from performing DE between cell-type clusters with Presto. f , Joint UMAP of Ultima and Illumina data colored as in b . We did not sample the exact same number of reads from Illumina or Ultima data since they have approximately the same number of total UMIs. NK, natural killer cells; CTL, cytotoxic T cells; TCM, central memory T cells; MAIT, mucosal-associated invariant T cells; Treg, regulatory T cells; dnT, double negative T cells; gdT, gamma delta T cells.

Article Snippet: Dotted line: 10 cells per guide. ( d ) UMAP of gene expression for Illumina. ( e ) Feature plot of the number of genes for Illumina. ( f ) Violin plots of DE genes among clusters in the Illumina data.

Techniques:

Journal: Nature Biotechnology

Article Title: Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing

doi: 10.1038/s41587-022-01452-6

Figure Lengend Snippet: ( a ) NMF applied to either Illumina, Ultima, or Illumina data with permuted genes, to extract the cell loadings, and test how well they fit either the Illumina (left) or Ultima (right) data, measured by Mean Squared Error (MSE; lower MSE is better). Dots show analysis repeated ten times with different seeds. ( b ) NMF applied to either Illumina, Ultima, or Illumina data with permuted genes, to extract the gene loadings, and test how well those loadings fit either the Illumina (left) or Ultima (right) data, measured by MSE. Dots as in ( a ). ( c ) Correlation between cell level loadings shown after applying cNMF on Illumina and Ultima data with 15 factors. ( d ) Correlation between gene level loadings shown after applying cNMF on Illumina and Ultima data with 15 factors. ( e ) Correlation between cell level loadings of both runs after applying cNMF on the same Illumina data twice with 15 factors. ( f ) Correlation between gene level loadings of both runs after applying cNMF on the same Illumina data twice with 15 factors. ( g ) Correlation between cell level loadings in the Illumina data after applying cNMF. ( h ) Correlation between gene level loadings in the Illumina data after applying cNMF. ( i ) Correlation between cell level loadings after performing cNMF on the PBMC Illumina and Perturb-Seq Illumina data with 15 factors and projecting the Perturb-Seq gene loadings onto the PBMC data to get cell loadings. ( j ) Correlation of gene level loadings after performing cNMF on PBMC Illumina and Perturb-Seq Illumina data with 15 factors. Feature plots of the cell level loading cNMF factors for Ultima ( k ) and Illumina ( l ) in the joint UMAP space. All correlations here are Pearson correlations.

Article Snippet: Dotted line: 10 cells per guide. ( d ) UMAP of gene expression for Illumina. ( e ) Feature plot of the number of genes for Illumina. ( f ) Violin plots of DE genes among clusters in the Illumina data.

Techniques:

Journal: Nature Biotechnology

Article Title: Mostly natural sequencing-by-synthesis for scRNA-seq using Ultima sequencing

doi: 10.1038/s41587-022-01452-6

Figure Lengend Snippet: ( a ) Histogram of the number of guide UMIs per cell from targeted PCR amplification PCR. ( b ) Histogram of the number of CITE-seq ADT UMIs per cell. ( c ) Histogram showing the number of guides with a given number of cells assigned to them. Note the y axis is log 10 scaled. Dotted line: 10 cells per guide. ( d ) UMAP of gene expression for Illumina. ( e ) Feature plot of the number of genes for Illumina. ( f ) Violin plots of DE genes among clusters in the Illumina data. Shown are clusters showing active cell cycling (cluster 0, 1, and 5) and a cluster with high immediate early gene levels (cluster 5). ( g ) UMAP of gene expression for Ultima. ( h ) Feature plot of the number of genes for Ultima. ( i ) Violin plots of DE genes among clusters in the Ultima data. ( j ) Scatterplot of -log 10 (p-value) for each guide/gene pair in Illumina vs. Ultima, where the p-values are the output of DE analysis comparing each guide to the control Intergenic_1 guide. ( k ) Scatterplot of logFC for each guide/gene pair as in ( j ). Only gene/guide pairs with uncorrected p-value < 0.01 in either Ultima or Illumina are shown.

Article Snippet: Dotted line: 10 cells per guide. ( d ) UMAP of gene expression for Illumina. ( e ) Feature plot of the number of genes for Illumina. ( f ) Violin plots of DE genes among clusters in the Illumina data.

Techniques: Amplification, Expressing, Control

Journal: bioRxiv

Article Title: An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization

doi: 10.1101/2024.07.18.604137

Figure Lengend Snippet: Each panel represents the distribution of the fluorescence intensity for each marker on the clustered UMAP. The MATLAB UMAP package is used for data analysis with default parameter setting (min_dist = 0.3, n_neighbors = 15, metric = Euclidean, randomize = 1).

Article Snippet: The UMAP package written in MATLAB ( ) is used for data analysis with default parameter setting (min_dist = 0.3, n_neighbors = 15, metric = Euclidean, randomize = 1).

Techniques: Fluorescence, Marker

Journal: Acta Neuropathologica Communications

Article Title: Spatio-temporal dynamics of microglia phenotype in human and murine cSVD: impact of acute and chronic hypertensive states

doi: 10.1186/s40478-023-01672-0

Figure Lengend Snippet: Chronic hypertension results in microglia dynamical changes in the hippocampus of hypertensive rats. Overlay of Uniform manifold approximation and projection (UMAP) map displaying randomly sub-sampled microglia cells from normotensive and hypertensive hippocampus analyzed by flow cytometry in ( a ) early and ( e ) late hypertension. ( b , f ) UMAP plot with color-coded Phenograph-guided clustering with cell identities established based on the investigated surface markers. Representative UMAP plots from normotensive and hypertensive brains displaying microglia sub-clusters corresponding to each cohort. ( c , g ) Relative frequencies of microglial cells and their respective percentages per cluster in early and late chronic hypertension. ( d , h ) Heat map displaying normalized median expression values for each population present in each color-coded cluster exhibiting dynamic expression of diverse microglia activation markers (CD200R, CD45, CD86, CD163, MHCII, CD11b/c, P2Y12R, CX3CR1) upon early and late chronic hypertension compared to their respective age-matched normotensive control. Ctrl, Controls; HTN, Hypertension. p -values: ** for p ≤ 0.01; *** for p ≤ 0.001; **** for p ≤ 0.0001

Article Snippet: Flowjo UMAP and Phenograph plugins.

Techniques: Flow Cytometry, Expressing, Activation Assay