哨兵表型代码选择（用于金黄色葡萄球菌感染全表型关联研究）

数据集获取（Figshare）

• 源站标题：Sentinel phecode selection.
• DOI：10.1371/journal.pone.0303395.s009
• 发布日期：2024-07-05
• 文件数：1 个
• 文件总体积：30.02 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Sentinel_phecode_selection_/26191742

命令行下载

curl -L -o "pone.0303395.s009.xlsx" "https://ndownloader.figshare.com/files/47458226"

文件清单

• pone.0303395.s009.xlsx（30.02 KB）

文件总体积 30.02 KB（源站 API 实测）。

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。

数据说明

Background
Phenome-Wide Association study (PheWAS) is a powerful tool designed to systematically screen clinical observations derived from medical records (phenotypes) for association with a variable of interest. Despite their usefulness, no systematic screening of phenotypes associated with Staphylococcusaureusinfections (SAIs) has been done leaving potential novel risk factors or complications undiscovered.
Method and cohorts
We tailored the PheWAS approach into a two-stage screening procedure to identify novel phenotypes correlating with SAIs. The first stage screened for co-occurrence of SAIs with other phenotypes within medical records. In the second stage, significant findings were examined for the correlations between their age of onset with that of SAIs. The PheWAS was implemented using the medical records of 754,401 patients from the Marshfield Clinic Health System. Any novel associations discovered were subsequently validated using datasets from TriNetX and All of Us, encompassing 109,884,571 and 118,538 patients respectively.
Results
Forty-one phenotypes met the significance criteria of a p-value 5. Out of these, we classified 23 associations either as risk factors or as complications of SAIs. Three novel associations were discovered and classified either as a risk (long-term use of aspirin) or complications (iron deficiency anemia and anemia of chronic disease). All novel associations were replicated in the TriNetX cohort. In the All of Us cohort, anemia of chronic disease was replicated according to our significance criteria.
Conclusions
The PheWAS of SAIs expands our understanding of SAIs interacting phenotypes. Additionally, the novel two-stage PheWAS approach developed in this study can be applied to examine other disease-disease interactions of interest. Due to the possibility of bias inherent in observational data, the findings of this study require further investigation.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0303395.s009（source: https://plos.figshare.com/articles/dataset/Sentinel_phecode_selection_/26191742）。