DOI: 10.6084/m9.figshare.21829905.v9
title: Datasets for single-cell-resolution spatial mapping by SC2Spa

description: <b>Title</b><br>Datasets for high resolution spatial mapping for SC2Spa<br><b>Author(s)</b><br>Linbu Liao<br><b>Categories</b><br>Bioinformatic methods development<br><b>Item type</b><br>dataset<br><b>Keyword(s)</b><br>Spatial transcriptomics, Spatial inference<br><b>File description</b><br>AdataMH1.h5ad is the processed mouse hippocampus spatial transcriptomics data file of puck_200115_08 from Slide-seqV2 paper[1].AMB_HC.h5ad is a processed mouse hippocampus scRNA-seq data file[2]. The datasets are saved in Anndata format.HC1_transfer_to_AMB.csv includes the predicted location of the scRNA-seq data (AMB_HC.h5ad). The columns "ClosestSC" and "Dis2ClosestBead" are used in the cell communication analysis tutorial.ssHippo_RCTD.csv is the annotation for the AdataMH1.h5ad file by RCTD[3].<br>WDs_T2.csv includes the Wasserstain distance of genes between the scRNA-seq dataset[2] and the mouse hippocampus Slide-seqV2[1] dataset.SI_T2_WD.h5 is the traned model for mapping mouse hippocampus cells to space. The model is trained using genes selected according to Wasserstain distance.SI_T2.h5 is the spatial inference model trained on all shared genes between two datasets.T2_stat.csv is a summary of SI_T2.h5. It contains genes' contribution to location prediction and Pearson's correlation between prediction and true gene expression.<br>AdataMH2.h5ad is the processed mouse hippocampus spatial transcriptomics data file of puck_191204_01 from the Slide-seqV2 paper[1].slideSeq_Puck190926_03_RCTD.csv is the annotation file for AdataEmbryo1.h5ad. AdataEmbryo1.h5ad is preprocessed file of puck_190926_03 (a mouse emrbyo Slide-seqV2[1] dataset).C2L.zip is the cell2location[4] data used in the analysis of SC2Spa manuscript.Cell2Location_ST.h5ad is the processed Visium adult mouse brain spatial transcriptomics data ST8059048 from Cell2Location paper[4].Cell2Location_snRNAseq.h5ad is the processed snRNA-seq adult mouse brain data of 5705STDY8058280, 5705STDY8058281, 5705STDY8058282, 5705STDY8058283, 5705STDY8058284, 5705STDY8058285 from Cell2Location paper[4]. 80, 81, 82 are from male 1 (female). 83, 84, 85 are from mouse 2 (male)The datasets were used for the spatial mapping of SC2Spa.<br><b>Repositories</b>The github website of SC2Spa: https://github.com/linbuliao/SC2SpaThe github repository for SC2Spa analysis: https://github.com/linbuliao/SC2Spa_Notebooks<b>Documentation</b>The Read the Docs website of SC2Spa: https://sc2spa.readthedocs.io/en/latest/<br><b>References</b>[1] Stickels RR, Murray E, Kumar P, Li J, Marshall JL, Di Bella DJ, Arlotta P, Macosko EZ, Chen F: <b>Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2.</b> <i>Nature Biotechnology</i> 2020.[2] Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H, Bien E, Baum M, Bortolin L, Wang SY, et al: <b>Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain.</b> <i>Cell</i> 2018, <b>174:</b>1015-+.[3] Cable DM, Murray E, Zou LS, Goeva A, Macosko EZ, Chen F, Irizarry RA: <b>Robust decomposition of cell type mixtures in spatial transcriptomics. </b>Nat Biotechnol 2021.[4] Kleshchevnikov V, Shmatko A, Dann E, Aivazidis A, King HW, Li T, Elmentaite R, Lomakin A, Kedlian V, Gayoso A, et al: <b>Cell2location maps fine-grained cell types in spatial transcriptomics.</b> <i>Nat Biotechnol</i> 2022, <b>40:</b>661-671.<br>