mouse olfactory bulb dataset  (Spatial Transcriptomics Inc)

Journal: Briefings in Bioinformatics

Article Title: SpaGIC: graph-informed clustering in spatial transcriptomics via self-supervised contrastive learning

doi: 10.1093/bib/bbae578

Figure Lengend Snippet: Spatial domains identification on the Stereo-seq MOB dataset. ( A ) The laminar structure of the Stereo-seq MOB annotated in DAPI-stained images. ( B ) Clustering results from Scanpy, SpaGCN, DeepST, STAGATE, GraphST, and SpaGIC. ( C ) Visualization of spatial domains detected by SpaGIC and related marker gene expression.

Article Snippet: Specifically, (i) the LIBD human dorsolateral prefrontal cortex (DLPFC) dataset: http://spatial.libd.org/spatialLIBD/ ; (ii) the 10x Visium human breast cancer dataset: https://www.10xgenomics.com/datasets/human-breast-cancer-block-a-section-1-1-standard-1-1-0 ; (iii) the anterior section of the 10x Visium mouse brain: https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-1-sagittal-anterior-1-standard-1-1-0 ; (iv) the Stereo-seq mouse olfactory bulb dataset: https://github.com/STOmics/SAW/tree/main/Test_Data ; (v) the Slide-seqV2 mouse olfactory bulb dataset: https://singlecell.broadinstitute.org/single_cell/study/SCP815/highly-sensitive-spatial-transcriptomics-at-near-cellular-resolution-with-slide-seqv2#study-summary ; (vi) the STARmap mouse visual cortex dataset: https://drive.google.com/drive/folders/1I1nxheWlc2RXSdiv24dex3YRaEh780my?usp=sharing ; (vii) the osmFISH mouse somatosensory cortex dataset: https://linnarssonlab.org/osmFISH/ .

Techniques: Staining, Marker, Gene Expression