相关实验视频

Updated: Jul 26, 2025

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

Published on: October 6, 2014

用人类染色体尺度长度变化计算的遗传风险评分的评估,以预测乳腺癌的发生

Charmeine Ko¹, James P Brody²

¹Department of Biomedical Engineering, University of California, Irvine, USA.

|June 16, 2023

概括

使用染色体尺度长度变化 (CSLV) 的新基因组分析显示,预测乳腺癌风险具有前途. 这种计算方法在英国生物库数据集中实现了高准确度 (AUC 0.836),有可能改善早期检测并降低死亡率.

科学领域:

基因组学就是基因组学.
计算生物学计算生物学
癌症研究癌症研究

背景情况:

准确的乳腺癌预测可以降低死亡率.
目前的预测模型 (家族史,BRCA,SNP分析) 的准确性有限 (AUC~0.65).
染色体尺度长度变化 (CSLV) 是一种新的基因组表征方法.

研究的目的:

开发和评估使用CSLV进行乳腺癌预测的机器学习模型.
在独立数据集中评估CSLV的预测性能.

主要方法:

机器学习模型使用来自英国生物银行和癌症基因组图谱 (TCGA) 的CSLV数据进行训练.
使用了两个数据集:英国生物库 (1534例,4391对照) 和TCGA (874例,3381对照).
模型性能使用接收器操作特征曲线 (AUC) 下的面积来评估.

主要成果:

一个基于CSLV的模型在英国生物库数据中实现了0.836的AUC (95%CI:0.830-0.843).
使用TCGA数据的类似模型的AUC为0.704 (95%CI:0.702-0.706).
变量重要性分析显示,没有单个染色体区域主导了预测能力.

结论:

CSLV是一种有效的基因组标记物,用于预测乳腺癌的发展.
这项回顾性研究使用英国生物银行数据证明了CSLV在乳腺癌风险评估中的潜力.

关键词:

乳腺癌乳腺癌乳腺癌副本数量变化的变化细菌线的细菌线是什么机器学习机器学习在TCGA中,它是TCGA.英国生物银行.在H2O的基础上,H2O是

更多相关视频

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

Published on: February 28, 2021

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

相关概念视频

Comparing Copy Number Variations and SNPs

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...