steinbock results of IMC example data

This repository hosts the results of processing example imaging mass cytometry (IMC) data hosted at zenodo.org/record/5949116 using the <em>steinbock </em>framework available at github.com/BodenmillerGroup/steinbock. Please refer to <strong>steinbock.sh </strong>for how these data were generated from the raw data. The following files are part of this repository: <strong>panel.csv</strong>: contains channel information regarding the used antibodies in <em>steinbock</em> format <strong>img.zip</strong>: contains hot pixel filtered multi-channel images derived from the IMC raw data. One file per acquisition is generated <strong>images.csv</strong>: contains metadata per acquisition <strong>pixel_classifier.ilp</strong>: ilastik pixel classifier (same as the one in zenodo.org/record/6043544) <strong>ilastik_crops.zip</strong>: image crops on which the ilastik classifier was trained (same as the ones in zenodo.org/record/6043544) <strong>ilastik_img.zip</strong>: contains multi-channel images (one per acquisition) in .h5 format for ilastik pixel classification <strong>ilastik_probabilities.zip</strong>: 3 channel images containing the pixel probabilities after pixel classification <strong>masks_ilastik.zip</strong>: segmentation masks derived from the ilastik pixel probabilities using the <strong>cell_segmentation.cppipe</strong> pipeline <strong>masks_deepcell.zip</strong>: segmentation masks derived by <em>deepcell</em> segmentation <strong>intensities.zip</strong>: Contains one .csv file per acquisition. Each file contains single-cell measures of the mean pixel intensity per cell and channel based on the files in <strong>img.zip </strong>and <strong>masks_deepcell.zip</strong>. <strong>regionprops.zip</strong>: Contains one .csv file per acquisition. Each file contains single-cell measures of the morphological features and location of cells based on <strong>masks_deepcell.zip</strong>. <strong>neighbors.zip</strong>: Contains one .csv file per acquisition. Each file contains an edge list of cell IDs indicating cells in close proximity based on <strong>masks_deepcell.zip</strong>. <strong>ome.zip</strong>: contains .ome.tiff files derived from img.zip; one file per acquisition <strong>histocat.zip</strong>: contains single-channel .tiff files with segmentation masks derived from <strong>masks_deepcell.zip</strong> for upload to histoCAT (bodenmillergroup.github.io/histoCAT) <strong>cells.csv</strong>: contains intensity and regionprop measurements of all cells <strong>cells_csv.zip</strong>: contains intensity and regionprop measurements of all cells per acquisition <strong>cells.fcs</strong>: contains intensity and regionprop measurements of all cells in fcs format <strong>cells_fcs.zip</strong>: contains intensity and regionprop measurements of all cells per acquisition in fcs format <strong>cells.h5ad</strong>: contains intensity, regionprop and neighbor measurements of all cells in <em>anndata </em>format <strong>cells_h5ad</strong>: contains intensity regionprop and neighbor measurements of all cells per acquisition in <em>anndata </em>format <strong>graphs.zip</strong>: contains spatial object graphs in .graphml format; one file per acquisition本仓库存储了对zenodo.org/record/5949116上的成像质谱流式细胞术（imaging mass cytometry, IMC）示例数据，使用BodenmillerGroup开发的<em>steinbock</em>框架（开源地址：github.com/BodenmillerGroup/steinbock）处理后的结果。请参阅<em>steinbock.sh</em>文件，了解如何从原始数据生成本仓库中的这批处理结果。 本仓库包含以下文件： 1. **panel.csv**：采用<em>steinbock</em>格式存储实验所用抗体的通道信息。 2. **img.zip**：包含从IMC原始数据经热像素过滤得到的多通道图像，每个成像采集任务对应一个独立文件。 3. **images.csv**：存储每个成像采集任务的元数据信息。 4. **pixel_classifier.ilp**：ilastik像素分类器（与zenodo.org/record/6043544中提供的分类器完全一致）。 5. **ilastik_crops.zip**：用于训练上述ilastik分类器的图像裁剪块（与zenodo.org/record/6043544中提供的裁剪块完全一致）。 6. **ilastik_img.zip**：包含用于ilastik像素分类的多通道图像，每个采集任务对应一个.h5格式文件。 7. **ilastik_probabilities.zip**：包含像素分类完成后生成的三通道像素概率图像。 8. **masks_ilastik.zip**：通过<em>cell_segmentation.cppipe</em>分析流程，从ilastik像素概率结果中提取得到的细胞分割掩码。 9. **masks_deepcell.zip**：通过<em>deepcell</em>细胞分割算法得到的细胞分割掩码。 10. **intensities.zip**：每个采集任务对应一个.csv格式文件。每个文件包含基于**img.zip**与**masks_deepcell.zip**中的数据，计算得到的单个细胞各通道平均像素强度的单细胞测量结果。 11. **regionprops.zip**：每个采集任务对应一个.csv格式文件。每个文件包含基于**masks_deepcell.zip**得到的单个细胞的形态特征与空间位置信息的单细胞测量结果。 12. **neighbors.zip**：每个采集任务对应一个.csv格式文件。每个文件包含基于**masks_deepcell.zip**生成的细胞邻接边列表，用于标记空间上邻近的细胞ID。 13. **ome.zip**：包含从**img.zip**转换得到的.ome.tiff格式图像文件，每个采集任务对应一个文件。 14. **histocat.zip**：包含从**masks_deepcell.zip**提取得到的单通道.tiff格式分割掩码文件，用于上传至histoCAT平台（bodenmillergroup.github.io/histoCAT）。 15. **cells.csv**：存储所有细胞的强度与区域属性综合测量数据。 16. **cells_csv.zip**：按成像采集任务分类，存储所有细胞的强度与区域属性测量数据的压缩包。 17. **cells.fcs**：以流式细胞术标准格式（Flow Cytometry Standard, FCS）存储所有细胞的强度与区域属性测量数据。 18. **cells_fcs.zip**：按成像采集任务分类，存储所有细胞的FCS格式强度与区域属性测量数据的压缩包。 19. **cells.h5ad**：以<em>anndata</em>格式存储所有细胞的强度、区域属性与邻域关系综合测量数据。 20. **cells_h5ad.zip**：按成像采集任务分类，存储所有细胞的<em>anndata</em>格式强度、区域属性与邻域关系测量数据的压缩包。 21. **graphs.zip**：包含.graphml格式的空间对象图，每个采集任务对应一个独立文件。