下一代MUT-MAP:高灵敏度高通量微流体芯片突变分析面板

基于微流体芯片MUT-MAP的11个基因120个体细胞突变检测数据集,适用于肿瘤高通量突变分析。

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2016-01-18 更新
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基因组BiochemistrydnaNucleic acidscell biologyMolecular cell biologygeneticsGene identification and analysisGenetic screensmutationClinical geneticsPersonalized medicineoncology
Next Generation MUT-MAP, a High-Sensitivity High-Throughput Microfluidics Chip-Based Mutation Analysis Panel

基本信息

模态
基因组
大小
0.000792005 GB
许可
CC BY 4.0
创建/更新时间
2016-01-18
版本
v1

资源简介

下一代MUT-MAP:高灵敏度高通量微流体芯片突变分析面板

【数据集背景】

本数据集源站标题为《Next Generation MUT-MAP, a High-Sensitivity High-Throughput Microfluidics Chip-Based Mutation Analysis Panel》。配套论文《Next Generation MUT-MAP, a High-Sensitivity High-Throughput Microfluidics Chip-Based Mutation Analysis Panel》发表于 PLoS ONE(2014),DOI:10.1371/journal.pone.0090761。源站首次发布:2014-03-21。

【数据内容】

源站原始描述:Molecular profiling of tumor tissue to detect alterations, such as oncogenic mutations, plays a vital role in determining treatment options in oncology. Hence, there is an increasing need for a robust and high-throughput technology to detect oncogenic hotspot mutations. Although commercial assays are available to detect genetic alterations in single genes, only a limited amount of tissue is often available from patients, requiring multiplexing to allow for simultaneous detection of mutations in…

【数据结构与技术规格】

文件数 3 个,合计 792.00 KB。Figure_S1.tif:image/tiff,732.23 KB。Table_S1.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,42.75 KB。Table_S2.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,17.03 KB。数据集 DOI:10.1371/journal.pone.0090761。

【主题与分类】

源站学科分类:Biological Sciences。主题标签:Biochemistry、dna、Nucleic acids、cell biology、Molecular cell biology、genetics、Gene identification and analysis、Genetic screens、mutation、Clinical genetics。

【适用方向】

组学数据适用于生物标志物发现与分子分型相关建模研究。

【获取与许可】

源站页面:https://plos.figshare.com/articles/dataset/_Next_Generation_MUT_MAP_a_High_Sensitivity_High_Throughput_Microfluidics_Chip_Based_Mutation_Analysis_Panel_/970061

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:B. Schleifman, Erica; Tam, Rachel; Patel, Rajesh; Tsan, Alison; Sumiyoshi, Teiko; Fu, Ling; et al. (2016). Next Generation MUT-MAP, a High-Sensitivity High-Throughput Microfluidics Chip-Based Mutation Analysis Panel. PLOS ONE. Dataset

【使用注意】

· 源站最后修改于 2023-06-02,引用时请注意版本时效。

官方服务

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从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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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)

命令行下载

curl -L -o "Figure_S1.tif" "https://ndownloader.figshare.com/files/1430225"
curl -L -o "Table_S1.xlsx" "https://ndownloader.figshare.com/files/1430226"
curl -L -o "Table_S2.xlsx" "https://ndownloader.figshare.com/files/1430227"

文件清单

  • Figure_S1.tif(732.23 KB)
  • Table_S1.xlsx(42.75 KB)
  • Table_S2.xlsx(17.03 KB)

文件总体积 792.00 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

Molecular profiling of tumor tissue to detect alterations, such as oncogenic mutations, plays a vital role in determining treatment options in oncology. Hence, there is an increasing need for a robust and high-throughput technology to detect oncogenic hotspot mutations. Although commercial assays are available to detect genetic alterations in single genes, only a limited amount of tissue is often available from patients, requiring multiplexing to allow for simultaneous detection of mutations in many genes using low DNA input. Even though next-generation sequencing (NGS) platforms provide powerful tools for this purpose, they face challenges such as high cost, large DNA input requirement, complex data analysis, and long turnaround times, limiting their use in clinical settings. We report the development of the next generation mutation multi-analyte panel (MUT-MAP), a high-throughput microfluidic, panel for detecting 120 somatic mutations across eleven genes of therapeutic interest (AKT1, BRAF, EGFR, FGFR3, FLT3, HRAS, KIT, KRAS, MET, NRAS, and PIK3CA) using allele-specific PCR (AS-PCR) and Taqman technology. This mutation panel requires as little as 2 ng of high quality DNA from fresh frozen or 100 ng of DNA from formalin-fixed paraffin-embedded (FFPE) tissues. Mutation calls, including an automated data analysis process, have been implemented to run 88 samples per day. Validation of this platform using plasmids showed robust signal and low cross-reactivity in all of the newly added assays and mutation calls in cell line samples were found to be consistent with the Catalogue of Somatic Mutations in Cancer (COSMIC) database allowing for direct comparison of our platform to Sanger sequencing. High correlation with NGS when compared to the SuraSeq500 panel run on the Ion Torrent platform in a FFPE dilution experiment showed assay sensitivity down to 0.45%. This multiplexed mutation panel is a valuable tool for high-throughput biomarker discovery in personalized medicine and cancer drug development.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0090761(source: https://plos.figshare.com/articles/dataset/_Next_Generation_MUT_MAP_a_High_Sensitivity_High_Throughput_Microfluidics_Chip_Based_Mutation_Analysis_Panel_/970061)。

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⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。

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