癌症易感基因致病突变:300例全基因组测序与终生电子健康记录患者调查
300例患者的全基因组测序与终生电子健康记录,用于分析60个癌症易感基因的致病突变及其临床关联。

基本信息
资源简介
癌症易感基因致病突变:300例全基因组测序与终生电子健康记录患者调查
【数据集背景】
本数据集源站标题为《Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records》。配套论文《Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records》发表于 PLOS ONE(2016),DOI:10.1371/journal.pone.0167847。源站首次发布:2016-12-08。
【数据内容】
源站原始描述:Background It is unclear whether and how whole-genome sequencing (WGS) data can be used to implement genomic medicine. Our objective is to retrospectively evaluate whether WGS can facilitate improving prevention and care for patients with susceptibility to cancer syndromes. Methods and Findings We analyzed genetic mutations in 60 autosomal dominant cancer-predisposition genes in 300 deceased patients with WGS data and nearly complete long-term (over 30 years) medical records. To infer biological…
【数据结构与技术规格】
文件数 2 个,合计 169.98 KB。S1 Table.xls:application/vnd.ms-excel,74.24 KB。S2 Table.xls:application/vnd.ms-excel,95.74 KB。数据集 DOI:10.1371/journal.pone.0167847。
【主题与分类】
源站学科分类:Space Science、Medicine、Cell Biology、Genetics、Pharmacology、Biotechnology。主题标签:SeqHBase software framework、population-wide WGS correlates、EHR、5 patients、BRCA、APC、WGS data、5 cancer-predisposing genes、NF、Lifetime Electronic Health Records Background。
【适用方向】
多模态数据适合跨模态对齐、融合建模与联合表征学习方向的研究。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/Pathogenic_Mutations_in_Cancer-Predisposing_Genes_A_Survey_of_300_Patients_with_Whole-Genome_Sequencing_and_Lifetime_Electronic_Health_Records/4298195
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:He, Karen Y.; Zhao, Yiqing; McPherson, Elizabeth W.; Li, Quan; Xia, Fan; Weng, Chunhua; et al. (2016). Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records. PLOS ONE. Dataset
【使用注意】
· 源站最后修改于 2023-06-01,引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:Pathogenic Mutations in Cancer-Predisposing Genes: A Survey of 300 Patients with Whole-Genome Sequencing and Lifetime Electronic Health Records
- DOI:10.1371/journal.pone.0167847
- 发布日期:2016-12-08
- 文件数:2 个
- 文件总体积:169.98 KB
- 源站页面:https://plos.figshare.com/articles/dataset/Pathogenic_Mutations_in_Cancer-Predisposing_Genes_A_Survey_of_300_Patients_with_Whole-Genome_Sequencing_and_Lifetime_Electronic_Health_Records/4298195
命令行下载
curl -L -o "S1 Table.xls" "https://ndownloader.figshare.com/files/7014212"
curl -L -o "S2 Table.xls" "https://ndownloader.figshare.com/files/7014221"
文件清单
S1 Table.xls(74.24 KB)S2 Table.xls(95.74 KB)
文件总体积 169.98 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
It is unclear whether and how whole-genome sequencing (WGS) data can be used to implement genomic medicine. Our objective is to retrospectively evaluate whether WGS can facilitate improving prevention and care for patients with susceptibility to cancer syndromes.
Methods and Findings
We analyzed genetic mutations in 60 autosomal dominant cancer-predisposition genes in 300 deceased patients with WGS data and nearly complete long-term (over 30 years) medical records. To infer biological insights from massive amounts of WGS data and comprehensive clinical data in a short period of time, we developed an in-house analysis pipeline within the SeqHBase software framework to quickly identify pathogenic or likely pathogenic variants. The clinical data of the patients who carried pathogenic and/or likely pathogenic variants were further reviewed to assess their clinical conditions using their lifetime EHRs. Among the 300 participants, 5 (1.7%) carried pathogenic or likely pathogenic variants in 5 cancer-predisposing genes: one in APC, BRCA1, BRCA2, NF1, and TP53 each. When assessing the clinical data, each of the 5 patients had one or more different types of cancers, fully consistent with their genetic profiles. Among these 5 patients, 2 died due to cancer while the others had multiple disorders later in their lifetimes; however, they may have benefited from early diagnosis and treatment for healthier lives, had the patients had genetic testing in their earlier lifetimes.
Conclusions
We demonstrated a case study where the discovery of pathogenic or likely pathogenic germline mutations from population-wide WGS correlates with clinical outcome. The use of WGS may have clinical impacts to improve healthcare delivery.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0167847(source: https://plos.figshare.com/articles/dataset/Pathogenic_Mutations_in_Cancer-Predisposing_Genes_A_Survey_of_300_Patients_with_Whole-Genome_Sequencing_and_Lifetime_Electronic_Health_Records/4298195)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
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