Datasets for single-cell-resolution spatial mapping by SC2Spa

<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)ModelCell2Location_snRNAseq2ST_SC2Spa_WD.h5 is is the pretrained SC2Spa model for mapping snRNAseq to ST (Genes with a Wasserstein Distance greater than 0.1 was used for training)WDs_snRNAseq2Visium.csv has the Wasserstain distance information of genes between the snRNA-seq data[4] and the Visium mouse brain data[4].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>

<b>标题</b><br>SC2Spa高分辨率空间映射专用数据集<br><b>作者</b><br>Linbu Liao<br><b>分类</b><br>生物信息学方法开发<br><b>资源类型</b><br>数据集<br><b>关键词</b><br>空间转录组学（Spatial transcriptomics），空间推断（Spatial inference）<br><b>文件说明</b><br>`AdataMH1.h5ad` 为来自Slide-seqV2研究[1]中puck_200115_08样本的经预处理的小鼠海马体空间转录组数据文件。<br>`AMB_HC.h5ad` 为经预处理的小鼠海马体单细胞RNA测序（scRNA-seq）数据文件[2]。<br>所有数据集均采用AnnData（Anndata）格式存储。<br>`HC1_transfer_to_AMB.csv` 包含单细胞RNA测序数据（`AMB_HC.h5ad`）的预测空间位置信息，其中`ClosestSC`与`Dis2ClosestBead`两列可用于细胞通信分析教程。<br>`ssHippo_RCTD.csv` 为通过RCTD方法[3]对`AdataMH1.h5ad`文件生成的注释文件。<br>`WDs_T2.csv` 包含单细胞RNA测序数据集[2]与小鼠海马体Slide-seqV2数据集[1]之间的基因瓦瑟斯坦距离（Wasserstein distance）信息。<br>`SI_T2_WD.h5` 为将小鼠海马体细胞映射至空间位置的预训练模型，该模型基于瓦瑟斯坦距离筛选得到的基因进行训练。<br>`SI_T2.h5` 为基于两个数据集的所有共有基因训练得到的空间推断模型。<br>`T2_stat.csv` 为`SI_T2.h5`的统计总结文件，其中包含基因对位置预测的贡献度，以及预测基因表达量与真实基因表达量之间的皮尔逊相关系数。<br>`AdataMH2.h5ad` 为来自Slide-seqV2研究[1]中puck_191204_01样本的经预处理的小鼠海马体空间转录组数据文件。<br>`slideSeq_Puck190926_03_RCTD.csv` 为`AdataEmbryo1.h5ad`的注释文件。`AdataEmbryo1.h5ad` 为puck_190926_03样本（小鼠胚胎Slide-seqV2数据集[1]）的预处理文件。<br>`C2L.zip` 为SC2Spa论文分析中使用的cell2location[4]相关数据。<br>`Cell2Location_ST.h5ad` 为来自cell2location研究[4]中ST8059048样本的经预处理的Visium成年小鼠大脑空间转录组数据文件。<br>`Cell2Location_snRNAseq.h5ad` 为来自cell2location研究[4]中5705STDY8058280、5705STDY8058281、5705STDY8058282、5705STDY8058283、5705STDY8058284、5705STDY8058285样本的经预处理的成年小鼠大脑单细胞核RNA测序（snRNA-seq）数据文件。其中80、81、82号样本来自雄性1（雌性），83、84、85号样本来自小鼠2（雄性）。<br>`ModelCell2Location_snRNAseq2ST_SC2Spa_WD.h5` 为将单细胞核RNA测序数据映射至空间转录组数据的预训练SC2Spa模型，训练时选用了瓦瑟斯坦距离大于0.1的基因。<br>`WDs_snRNAseq2Visium.csv` 包含单细胞核RNA测序数据集[4]与Visium小鼠大脑数据集[4]之间的基因瓦瑟斯坦距离信息。<br>本数据集套件均用于SC2Spa的空间映射分析。<br><b>存储库</b><br>SC2Spa的GitHub网站：https://github.com/linbuliao/SC2Spa<br>SC2Spa分析代码GitHub仓库：https://github.com/linbuliao/SC2Spa_Notebooks<br><b>文档</b><br>SC2Spa的Read the Docs文档网站：https://sc2spa.readthedocs.io/en/latest/<br><b>参考文献</b><br>[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.<br>[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-+.<br>[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> <i>Nat Biotechnol</i> 2021.<br>[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.