Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools.
<p><b>(A–D)</b> Spatial architectures of human Lung (A), Breast (B and C), and Intestinal (D) tissues reconstructed by Cell2Spatial, CytoSPACE, CellTrek, Tangram, and Seurat. Each dot represents an individual cell and cell types are marked by color codes. <b>(E–H)</b> S...
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| مؤلفون آخرون: | , , , , , , , , |
| منشور في: |
2025
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| _version_ | 1852014774989094912 |
|---|---|
| author | Huamei Li (8815955) |
| author2 | Jingchao Liu (2051245) Guige Wang (22634210) Zhenyu Liu (179092) Meng Cao (105914) Lingyun Sun (255929) Cheng Peng (118834) Yiyao Liu (554854) Liang Ma (37793) Qing Xiong (136442) |
| author2_role | author author author author author author author author author |
| author_facet | Huamei Li (8815955) Jingchao Liu (2051245) Guige Wang (22634210) Zhenyu Liu (179092) Meng Cao (105914) Lingyun Sun (255929) Cheng Peng (118834) Yiyao Liu (554854) Liang Ma (37793) Qing Xiong (136442) |
| author_role | author |
| dc.creator.none.fl_str_mv | Huamei Li (8815955) Jingchao Liu (2051245) Guige Wang (22634210) Zhenyu Liu (179092) Meng Cao (105914) Lingyun Sun (255929) Cheng Peng (118834) Yiyao Liu (554854) Liang Ma (37793) Qing Xiong (136442) |
| dc.date.none.fl_str_mv | 2025-11-17T18:38:49Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pbio.3003477.s007 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Comparative_analysis_of_spatial_architectures_and_cellular_proportions_in_Lung_Breast_and_Intestinal_tissues_recovered_by_different_mapping_tools_/30641972 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Cell Biology Molecular Biology Neuroscience Biotechnology Developmental Biology Cancer Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified synthetic data demonstrated reconstructing tissue architectures minimizing assignment algorithm method integrates information improve signal fidelity effectively delineating fine 10 &# 215 theoretic gene selection incomplete gene capture spatial transcriptomic spots spatial hotspot detection segments spatial spots scale spatial patterns lacks spatial context handling unmatched datasets balances transcriptional similarity xlink "> single maps single cells results highlight cell2spatial cell2spatial incorporates neural gene complexity spatial transcriptomics spatial proximity spatial organization spatial coherence transcriptional heterogeneity developed cell2spatial st datasets visium hd versatile framework powerful tool particular strength mouse kidney human thymus guided clustering fully matched enhance scalability developmental trajectories computational framework complex tissues cellular function cellular compositions analytical scope |
| dc.title.none.fl_str_mv | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p><b>(A–D)</b> Spatial architectures of human Lung (A), Breast (B and C), and Intestinal (D) tissues reconstructed by Cell2Spatial, CytoSPACE, CellTrek, Tangram, and Seurat. Each dot represents an individual cell and cell types are marked by color codes. <b>(E–H)</b> Scatter plots showing the consistency between the cellular proportions in spatial architectures reconstructed with various mapping tools and the cellular compositions predicted by CARD spatial deconvolution tool [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003477#pbio.3003477.ref011" target="_blank">11</a>]. The blue line denotes the linear fit, and the shaded area represents the 95% confidence interval. Different colors of points indicate distinct cell types. “<i>R</i>” represents the Pearson correlation coefficient (PCC). <i>P</i>-values were obtained by two-sided <i>t</i>-tests. (E) Lung; (F) BRCA.1; (G) BRCA.2; (H) Intestinal. <b>(I)</b> Table summarizing the number of cell types effectively mapped to spatial locations by each tool. “Reference” represents the total number of cell types in the single-cell atlas of the human tissues. The underlying data for this figure can be found at <a href="https://zenodo.org/records/17212677" target="_blank">https://zenodo.org/records/17212677</a>.</p> <p>(TIF)</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_2fc60930ed4befa03a59bdccc151bb72 |
| identifier_str_mv | 10.1371/journal.pbio.3003477.s007 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30641972 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools.Huamei Li (8815955)Jingchao Liu (2051245)Guige Wang (22634210)Zhenyu Liu (179092)Meng Cao (105914)Lingyun Sun (255929)Cheng Peng (118834)Yiyao Liu (554854)Liang Ma (37793)Qing Xiong (136442)Cell BiologyMolecular BiologyNeuroscienceBiotechnologyDevelopmental BiologyCancerPlant BiologyEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedsynthetic data demonstratedreconstructing tissue architecturesminimizing assignment algorithmmethod integrates informationimprove signal fidelityeffectively delineating fine10 &# 215theoretic gene selectionincomplete gene capturespatial transcriptomic spotsspatial hotspot detectionsegments spatial spotsscale spatial patternslacks spatial contexthandling unmatched datasetsbalances transcriptional similarityxlink "> singlemaps single cellsresults highlight cell2spatialcell2spatial incorporates neuralgene complexityspatial transcriptomicsspatial proximityspatial organizationspatial coherencetranscriptional heterogeneitydeveloped cell2spatialst datasetsvisium hdversatile frameworkpowerful toolparticular strengthmouse kidneyhuman thymusguided clusteringfully matchedenhance scalabilitydevelopmental trajectoriescomputational frameworkcomplex tissuescellular functioncellular compositionsanalytical scope<p><b>(A–D)</b> Spatial architectures of human Lung (A), Breast (B and C), and Intestinal (D) tissues reconstructed by Cell2Spatial, CytoSPACE, CellTrek, Tangram, and Seurat. Each dot represents an individual cell and cell types are marked by color codes. <b>(E–H)</b> Scatter plots showing the consistency between the cellular proportions in spatial architectures reconstructed with various mapping tools and the cellular compositions predicted by CARD spatial deconvolution tool [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003477#pbio.3003477.ref011" target="_blank">11</a>]. The blue line denotes the linear fit, and the shaded area represents the 95% confidence interval. Different colors of points indicate distinct cell types. “<i>R</i>” represents the Pearson correlation coefficient (PCC). <i>P</i>-values were obtained by two-sided <i>t</i>-tests. (E) Lung; (F) BRCA.1; (G) BRCA.2; (H) Intestinal. <b>(I)</b> Table summarizing the number of cell types effectively mapped to spatial locations by each tool. “Reference” represents the total number of cell types in the single-cell atlas of the human tissues. The underlying data for this figure can be found at <a href="https://zenodo.org/records/17212677" target="_blank">https://zenodo.org/records/17212677</a>.</p> <p>(TIF)</p>2025-11-17T18:38:49ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pbio.3003477.s007https://figshare.com/articles/figure/Comparative_analysis_of_spatial_architectures_and_cellular_proportions_in_Lung_Breast_and_Intestinal_tissues_recovered_by_different_mapping_tools_/30641972CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306419722025-11-17T18:38:49Z |
| spellingShingle | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. Huamei Li (8815955) Cell Biology Molecular Biology Neuroscience Biotechnology Developmental Biology Cancer Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified synthetic data demonstrated reconstructing tissue architectures minimizing assignment algorithm method integrates information improve signal fidelity effectively delineating fine 10 &# 215 theoretic gene selection incomplete gene capture spatial transcriptomic spots spatial hotspot detection segments spatial spots scale spatial patterns lacks spatial context handling unmatched datasets balances transcriptional similarity xlink "> single maps single cells results highlight cell2spatial cell2spatial incorporates neural gene complexity spatial transcriptomics spatial proximity spatial organization spatial coherence transcriptional heterogeneity developed cell2spatial st datasets visium hd versatile framework powerful tool particular strength mouse kidney human thymus guided clustering fully matched enhance scalability developmental trajectories computational framework complex tissues cellular function cellular compositions analytical scope |
| status_str | publishedVersion |
| title | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| title_full | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| title_fullStr | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| title_full_unstemmed | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| title_short | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| title_sort | Comparative analysis of spatial architectures and cellular proportions in Lung, Breast, and Intestinal tissues recovered by different mapping tools. |
| topic | Cell Biology Molecular Biology Neuroscience Biotechnology Developmental Biology Cancer Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified synthetic data demonstrated reconstructing tissue architectures minimizing assignment algorithm method integrates information improve signal fidelity effectively delineating fine 10 &# 215 theoretic gene selection incomplete gene capture spatial transcriptomic spots spatial hotspot detection segments spatial spots scale spatial patterns lacks spatial context handling unmatched datasets balances transcriptional similarity xlink "> single maps single cells results highlight cell2spatial cell2spatial incorporates neural gene complexity spatial transcriptomics spatial proximity spatial organization spatial coherence transcriptional heterogeneity developed cell2spatial st datasets visium hd versatile framework powerful tool particular strength mouse kidney human thymus guided clustering fully matched enhance scalability developmental trajectories computational framework complex tissues cellular function cellular compositions analytical scope |