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Journal: Nucleic Acids Research
Article Title: CSsingle: a unified tool for robust decomposition of bulk and spatial transcriptomic data across diverse single-cell references
doi: 10.1093/nar/gkag410
Figure Lengend Snippet: CSsingle improves cross-source deconvolution. ( A ) Jitter plots displaying true and estimated cell type proportions in pancreatic islet. Each color represents a benchmarked method. Healthy subjects are denoted as dots while T2D subjects are denoted as triangles. ( B ) Decomposition benchmark of human PBMC using scRNA-seq reference data derived from six distinct scRNA-seq methods (10x Chromium v2, 10x Chromium v3, CEL-seq2, Drop-seq, inDrops, and Seq-Well).
Article Snippet: ,
Techniques: Derivative Assay
Journal: Briefings in Bioinformatics
Article Title: Cross-modality representation and multi-sample integration of spatially resolved omics data
doi: 10.1093/bib/bbag214
Figure Lengend Snippet: PRESENT facilitates accurate spatial domain identification in spatial RNA-ADT data. (a) spatial visualization of the 10x Genomics Visium RNA-protein human lymph node sample colored by ground truth domain labels. (b) Quantitative comparison of spatial domain identification performance between PRESENT and other baseline methods, shown as a bar plot for the human lymph node dataset. (c) Quantitative comparison between PRESENT utilizing both RNA and ADT data (RNA & ADT) and PRESENT using only RNA (RNA-only) or ADT data (ADT-only), shown as a radar plot in the human lymph node dataset. (d) UMAP visualization of latent embeddings from different methods, colored by ground truth domain labels in the human lymph node dataset. (e) UMAP visualization of latent embeddings, colored by cluster labels in the human lymph node dataset. (f) Spatial visualization of spots colored by cluster labels in the human lymph node dataset. The cluster labels in e and f were derived from latent embeddings of different methods using the Leiden algorithm. (g) Histology image of the SPOTS mouse spleen dataset and spatial visualization of spots colored by cluster labels in the SPOTS mouse spleen dataset. The cluster labels were derived from latent embeddings of PRESENT using Leiden algorithm. (h) Differentially expressed proteins of each spatial domain through one-versus-all Wilcoxon rank-sum test, shown as a dot plot. (i) DEGs of all the spatial domains through one-versus-all Wilcoxon rank-sum test, shown as a dot plot. (j) Volcano plot showing the DEGs of Mac1-enriched domain and Mac2-enriched domain through Mac1-versus-Mac2 Wilcoxon rank-sum test, where the x axis denotes the log(fold-change) (log(FC)), while the y axis denotes the significance measured by -log10(false discovery rate) (−log10(FDR)). The vertical dashed line represents the threshold for log(FC)= \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} $\pm$\end{document} 0.2, while the horizontal dashed line denotes the threshold for -log10(FDR) = 0.05. (k) Chord plot demonstrating the linkage of DEGs in the Mac1-enriched domain and the corresponding enriched pathways. The left semicircle represents DEGs while the right semicircle denotes the enriched biological processes. Bar plot is employed to demonstrate the significance of each pathway (x axis, −log10(FDR)). (l) The linkage of DEGs in the Mac2-enriched domain and corresponding pathways as well as the significance of each enriched pathway.
Article Snippet: The
Techniques: Comparison, Derivative Assay
Journal: Briefings in Bioinformatics
Article Title: Cross-modality representation and multi-sample integration of spatially resolved omics data
doi: 10.1093/bib/bbag214
Figure Lengend Snippet: PRESENT integrates single-omics samples of multiple developmental stages or dissected areas. (a) The quantitative evaluation of different integration methods on the three spatial ATAC mouse embryo samples using 14 metrics divided into two categories, namely batch effect removal and biological variance conservation. The category scores of these two aspects were calculated by averaging the metrics within each category. An overall score for each integration method was computed using a 40/60 weighted mean of the category scores for batch effect removal and biological variance conservation. (b) The spatial visualization of spots across the three spatial ATAC mouse embryo samples colored by ground truth spatial domains. (c) The spatial visualization of spots across the three spatial ATAC mouse embryo samples colored by the spatial clusters identified based on different integration methods. The first, second and third row of b and c denotes the samples from E12.5, E13.5 and E15.5 stages, respectively. (d) The anatomic annotation of the sagittal region in P56 mouse brain provided by Allen Reference Atlas . (e) The joint spatial clustering results based on the latent embeddings obtained by STAligner on the two horizontal mouse brain sagittal samples generated by the 10x Genomics Visium platform. (f) The joint spatial clustering results based on the latent embeddings obtained by GraphST on the two horizontal mouse brain sagittal samples generated by the 10x Genomics Visium platform. (g) The joint spatial clustering results based on the latent embeddings obtained by PRESENT on the two horizontal mouse brain sagittal samples generated by the 10x Genomics Visium platform.
Article Snippet: The
Techniques: Generated