Journal: Cell Reports Methods

Article Title: WEST is an ensemble method for spatial transcriptomics analysis

doi: 10.1016/j.crmeth.2024.100886

Figure Lengend Snippet: Performance on the Visium mouse brain data Two Visium datasets of mouse brains were used to test the performance of WEST. (A) The manually annotated domains of the mouse brain tissue with a fluorescence image. (B) The manually annotated domains of the mouse brain tissue with an H&E image. (C) Comparison of the performance between WEST and the other methods on the fluorescence data. (D) Comparison of the performance between WEST and the other methods on the H&E data.

Article Snippet: To evaluate the performance of WEST in real datasets, we analyze a publicly available 10X Genomics Visium dataset obtained from the human dorsolateral prefrontal cortex (DLPFC) study.

Techniques: Fluorescence, Comparison

Journal: Cell Reports Methods

Article Title: WEST is an ensemble method for spatial transcriptomics analysis

doi: 10.1016/j.crmeth.2024.100886

Figure Lengend Snippet:

Article Snippet: To evaluate the performance of WEST in real datasets, we analyze a publicly available 10X Genomics Visium dataset obtained from the human dorsolateral prefrontal cortex (DLPFC) study.

Techniques: Fluorescence, Software

Journal: Communications Biology

Article Title: Chrysalis: decoding tissue compartments in spatial transcriptomics with archetypal analysis

doi: 10.1038/s42003-024-07165-7

Figure Lengend Snippet: a Human breast cancer H&E image and the projection of the tissue compartments identified by Chrysalis (scale bar: 500 µm). b Boxplots of Pearson’s r values calculated between the reference cell type abundances from the Xenium measurement and the tissue compartment scores for the six methods applied to the human breast cancer dataset (centre line: median, box limits: upper and lower quartiles, whiskers: 1.5x interquartile range, diamonds: outliers, black dot: average value). c Correlation heatmap showing Pearson’s r between the cell type abundance data of 20 cell types derived from the subsequent tissue section measured with Xenium and the tissue compartments inferred by Chrysalis. d Individual Chrysalis Compartments 0, 2, 4, and 6 denoting DCIS #1, invasive tumour, myoepithelial, and DCIS #2 signatures, respectively. e Top 20 genes that contribute the most to Compartments 0, 2, 4, and 6 in the human breast cancer dataset. f Chrysalis compartments with integrated morphological features extracted with a deep autoencoder. Morphological features improved the separation between the adipose tissue (yellow), invasive tumour (red), and stroma (purple; right panels). g Tissue compartments within the mouse brain identified by Chrysalis. The white rectangle highlights the 5 cortical layer-associated tissue compartments. Cortical layer-associated tissue compartment scores in expert-annotated regions. h Chrysalis MIP plot of the two-sample mouse brain dataset and individual compartments corresponding to the fibre tracts (Compartment 0), internal granular layer of the cerebellum (Compartment 1), and ventral (Compartment 7) and dorsal (Compartment 3) cortex. i Chrysalis MIP of a human colorectal cancer sample captured with Visium HD and individual compartments showcasing distinct cellular niches: muscular layer (Compartment 7), fibroblastic stroma (Compartment 12), stromal immune infiltrates (Compartment 11), neoplastic epithelium (Compartment 4). j MIP of Chrysalis compartments in the mouse embryo (E12.5) captured with Stereo-seq and the compartments corresponding to the developing heart (Compartment 8) and brain (Compartment 9) alongside their corresponding top-weighted genes.

Article Snippet: 10x Visium datasets used in this study, including the human lymph node, the mouse brain FFPE coronal, the FF anterior, and posterior sagittal sections, and the Visium HD colorectal cancer are available on the 10x Genomics online data repository ( https://www.10xgenomics.com/resources/datasets ).

Techniques: Derivative Assay