MSBB与ROSMAP队列阿尔茨海默病韧性研究数据集

数据集获取

源站：https://synapse.org/Synapse:syn64153686

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

###The MSBB and ROSMAP Cohort AD Resilience Study Study name: The MSBB and ROSMAP Cohort AD Resilience Study **Abbreviation of study: **MSBB_ ROSMAP AD_resilience Human cohort: The MSBB and ROSMAP Cohort AD Resilience Study (MSBB ROSMAP _ AD_resilience, in short) is a multi-omics dataset comprising matched transcriptomic and proteomic profiles derived from postmortem prefrontal cortex (PFC) tissue of neurologically normal individuals without clinical or pathological evidence of Alzheimer’s disease (AD). The dataset includes 170 bulk RNA sequencing (RNA-seq) samples and 282 tandem mass tag (TMT)-based quantitative proteomic profiles, enabling integrative analyses across molecular layers. More specifically, the Mount Sinai Brain Bank (MSBB) study1 and the Religious Orders Study and Memory and Aging Project (ROSMAP) Study2 contributed 82 and 88 RNA-seq samples, along with 82 and 200 TMT-based proteomic profiles, respectively. Study participants are stratified into two aging groups: young-old (YO; 60–84 years) and oldest-old (OO; ≥85 years), to facilitate the investigation of age-associated molecular signatures and mechanisms of resilience to AD pathology. In addition to transcriptomic and proteomic measurements, matched whole-genome sequencing (WGS) data are available for most subjects that were previously generated, providing a genomic framework for downstream multi-omics integration and systems-level analyses. Reference List 1. Wang, M. et al. The Mount Sinai cohort of large-scale genomic, transcriptomic, and proteomic data in Alzheimer’s disease. Sci Data 5, 180185 (2018). https://doi.org:10.1038/sdata.2018.185 2. Bennett, D. A., Schneider, J. A., Arvanitakis, Z. & Wilson, R. S. Overview and findings from the religious orders study. Curr Alzheimer Res 9, 628-645 (2012). https://doi.org:10.2174/156720512801322573

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。