merfish dataset Search Results


merfish dataset  (Allen Institute for Brain Science)
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Allen Institute for Brain Science merfish dataset
a, CellMemory can characterize single-cell spatial omics from various sequencing platforms, including CosMx, <t>MERFISH,</t> Slide-seq, Stereo-seq, Xenium, and Slide-tags. b, The accuracy of spatial annotation tools is evaluated using datasets from mHypo (mouse hypothalamus measured by MERFISH), hNSCLC (human NSCLC measured by CosMx), and msSermato (mouse spermatogenesis measured by Slide-seq). Each dataset comprised three samples for replication. c, CellMemory was trained using single-cell data at the L2 cell type resolution, to generate CLS embeddings and annotations for Slide-tags cells. The right part is plotted by the L1 (original) and L2 (CellMemory) cell types in spatial coordinates. d, CellMemory model was built using single-cell data at the L3 resolution, to integrate single-cell and Slide-tags data. e, The cells highlighted in the co-embedding are Slide-tags cells, labeled with Slide-tags cell, L1 (original), L2 (CellMemory), and L3 (CellMemory) cell identity. f, The identification of Slide-tags cells at L3 resolution by CellMemory (L4 IT_2 and Micro-PVM_1) is displayed (the first line), along with the expression (the second line) and memory score (the third line) of TAGs ( VWC2L, F13A1 ). The left half represents the spatial coordinate, and the right half is the UMAP coordinate. g, UMAP representation of 4 million mouse whole brain cells from MERFISH, colored by subclasses. h, Annotation benchmark comparison of CellMemory with other state-of-art methods, including scGPT, Geneformer, and CellTypist. The reference dataset consists of mouse whole-brain 10x single-cell data, the query set comprises MERFISH cells derived from 59 coronal sections. i, Visualization of the 5 (total 59) mouse whole-brain sections, with cells colored by predictions of CellMemory. j, Spatial coordinates of mouse brain MERFISH section 36, colored by CellMemory predictions. k, Heatmap displaying the memory scores of TAGs for all subclasses of IT-ET Glut in section 36. l, Distribution of subclasses and their corresponding TAGs’ memory scores within the spatial coordinates of section 36.
Merfish Dataset, supplied by Allen Institute for Brain Science, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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a, CellMemory can characterize single-cell spatial omics from various sequencing platforms, including CosMx, MERFISH, Slide-seq, Stereo-seq, Xenium, and Slide-tags. b, The accuracy of spatial annotation tools is evaluated using datasets from mHypo (mouse hypothalamus measured by MERFISH), hNSCLC (human NSCLC measured by CosMx), and msSermato (mouse spermatogenesis measured by Slide-seq). Each dataset comprised three samples for replication. c, CellMemory was trained using single-cell data at the L2 cell type resolution, to generate CLS embeddings and annotations for Slide-tags cells. The right part is plotted by the L1 (original) and L2 (CellMemory) cell types in spatial coordinates. d, CellMemory model was built using single-cell data at the L3 resolution, to integrate single-cell and Slide-tags data. e, The cells highlighted in the co-embedding are Slide-tags cells, labeled with Slide-tags cell, L1 (original), L2 (CellMemory), and L3 (CellMemory) cell identity. f, The identification of Slide-tags cells at L3 resolution by CellMemory (L4 IT_2 and Micro-PVM_1) is displayed (the first line), along with the expression (the second line) and memory score (the third line) of TAGs ( VWC2L, F13A1 ). The left half represents the spatial coordinate, and the right half is the UMAP coordinate. g, UMAP representation of 4 million mouse whole brain cells from MERFISH, colored by subclasses. h, Annotation benchmark comparison of CellMemory with other state-of-art methods, including scGPT, Geneformer, and CellTypist. The reference dataset consists of mouse whole-brain 10x single-cell data, the query set comprises MERFISH cells derived from 59 coronal sections. i, Visualization of the 5 (total 59) mouse whole-brain sections, with cells colored by predictions of CellMemory. j, Spatial coordinates of mouse brain MERFISH section 36, colored by CellMemory predictions. k, Heatmap displaying the memory scores of TAGs for all subclasses of IT-ET Glut in section 36. l, Distribution of subclasses and their corresponding TAGs’ memory scores within the spatial coordinates of section 36.

Journal: bioRxiv

Article Title: Hierarchical Interpretation of Out-of-Distribution Cells Using Bottlenecked Transformer

doi: 10.1101/2024.12.17.628533

Figure Lengend Snippet: a, CellMemory can characterize single-cell spatial omics from various sequencing platforms, including CosMx, MERFISH, Slide-seq, Stereo-seq, Xenium, and Slide-tags. b, The accuracy of spatial annotation tools is evaluated using datasets from mHypo (mouse hypothalamus measured by MERFISH), hNSCLC (human NSCLC measured by CosMx), and msSermato (mouse spermatogenesis measured by Slide-seq). Each dataset comprised three samples for replication. c, CellMemory was trained using single-cell data at the L2 cell type resolution, to generate CLS embeddings and annotations for Slide-tags cells. The right part is plotted by the L1 (original) and L2 (CellMemory) cell types in spatial coordinates. d, CellMemory model was built using single-cell data at the L3 resolution, to integrate single-cell and Slide-tags data. e, The cells highlighted in the co-embedding are Slide-tags cells, labeled with Slide-tags cell, L1 (original), L2 (CellMemory), and L3 (CellMemory) cell identity. f, The identification of Slide-tags cells at L3 resolution by CellMemory (L4 IT_2 and Micro-PVM_1) is displayed (the first line), along with the expression (the second line) and memory score (the third line) of TAGs ( VWC2L, F13A1 ). The left half represents the spatial coordinate, and the right half is the UMAP coordinate. g, UMAP representation of 4 million mouse whole brain cells from MERFISH, colored by subclasses. h, Annotation benchmark comparison of CellMemory with other state-of-art methods, including scGPT, Geneformer, and CellTypist. The reference dataset consists of mouse whole-brain 10x single-cell data, the query set comprises MERFISH cells derived from 59 coronal sections. i, Visualization of the 5 (total 59) mouse whole-brain sections, with cells colored by predictions of CellMemory. j, Spatial coordinates of mouse brain MERFISH section 36, colored by CellMemory predictions. k, Heatmap displaying the memory scores of TAGs for all subclasses of IT-ET Glut in section 36. l, Distribution of subclasses and their corresponding TAGs’ memory scores within the spatial coordinates of section 36.

Article Snippet: CellMemory was trained using 781 scRNA-seq libraries, encompassing 4 million single-cell transcriptomes from the mouse brain, to analyze the Allen Institute for Brain Science (AIBS) MERFISH dataset .

Techniques: Sequencing, Labeling, Expressing, Comparison, Derivative Assay