含成纤维细胞与NMU调控肺腺癌细胞直接混合的体外共培养模型单细胞基因表达分析

数据集获取

源站：https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE240911

标准获取流程：

1. 访问源站链接，注册/登录账号；
2. 进入数据集详情页，按页面指引申请权限或直接下载；
3. 部分平台提供 SDK，例如：
   • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
   • ModelScope: pip install modelscope 后 modelscope download
   • 天池: 登录后页面提供直链下载
     以源站「数据下载/使用文档」页面为准。

数据说明

NMU gene expression was known to be over-represented in lung adenocarcinoma and negatively associated with overall survival or progression-free survival of patients. However, the mechanism(s) underlying the oncogenic roles of NMU are still not clear. Based on the transcriptome analysis of bulk-tissue of lung cancer datasets in the public domain, we found that NMU expression was significantly associated with those of some pro-fibrotic genes. Using subcutaneous mice xenograft model of human lung adenocarcinoma cells, we found significant increase of fibrotic phenotypes in xenograft derived from cell lines over-expressing NMU, including expression levels of marker proteins of myofibroblast, activation of fibroblast migration, and number of cells with morphology of fibroblast, while these changes can be reversed by knocking down the NMU expression of lung cancer cell lines. These suggest NMU from lung cancer cells may contribute to fibrosis of tumor microenvironment by recruiting and activating fibroblast and/or myofibroblast. Here we perform single-cell analysis of cell mixture containing co-cultured lung cancer cells and fibroblast cells.

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。