伊朗家系遗传性眼病全外显子测序临床基因组与表型数据集

数据集获取

源站：https://doi.org/10.5281/zenodo.18436043

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

Dataset Title:“Clinical, Genomic, and Phenotypic Dataset from a Whole-Exome Sequencing Study of Idiopathic Inherited Ocular Disorders in Iranian Families” Description:This dataset contains the complete de-identified clinical and genomic data supporting the findings of the manuscript entitled “Diagnostic Yield and Variant Spectrum of Whole-Exome Sequencing in Iranian Probands with Congenital and Early-Onset Ocular Disorders” . The data were generated from a whole-exome sequencing study of Iranian families with idiopathic inherited ocular disorders. The dataset comprises four structured tables (provided as Excel files) and a Readme guide: 1. Clinical and Demographic Characteristics of Probands2. Genotype-Phenotype Correlations3. Incidental variants identified by targeted exome sequencing4. Full Significant Variant List Data Context & Limitations: · This study is based on clinically annotated VCF files received from our sequencing service provider. Our primary contribution involved the detailed interpretation of these variants, genotype-phenotype correlation analysis, and determining their clinical significance.· Due to severe internet infrastructure restrictions in Iran, public deposition in specialized genomic repositories (EGA, ENA, dbGaP) was technically impossible.· This dataset provides all processed data necessary to reproduce the study’s analyses and conclusions. Contact Information: Corresponding Author: Dr.Ahmad Ebrahimi Email:Ahmadebrahimi64@gmail.com First Author,Corresponding Author : Ali Asadi,MSc Email: A-asadi@alumnus.tums.ac.ir- Daliasadi3165@gmail.com Citation: Published version:https://doi.org/10.1016/j.ymgmr.2026.101339

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。