在临床变异分析中的潜在陷的分类学图表,基于真实世界的证据
Adam Coovadia1, Luigi Boccuto1, Yenui Chang1
1College of Behavioral, Social and Health Sciences, Clemson University, Clemson, South Carolina, United States of America.
PloS one
|November 30, 2023
概括
基因变异的解释在实验室之间有所不同,导致数据库和文献中的错误. 本研究确定了变量分析资源中的陷,并提出了一种改善准确性和专业能力的模型.
科学领域:
- 临床遗传学 临床遗传学
- 生物信息学是一种生物信息学.
- 医疗信息学 医疗信息学
背景情况:
- 临床遗传实验室在与疾病相关的遗传变异的分类和解释方面表现出差异性.
- 遗传变体解释中的不一致性可以在科学文献和公共数据库中引入错误.
- 对于序列变异分析的现有资源可能包含固有的陷,影响诊断准确性.
研究的目的:
- 为序列变异分析引入公共和商业资源潜在陷的分类方案.
- 在临床实验室中解决遗传变异分类和解释的变异性.
- 提高文献和数据库中介绍的遗传发现的准确性和可靠性.
主要方法:
- 使用现实世界的证据进行定性研究.
- 开发一个分类学方案的变体分析陷.
- 人类错误的理性模型的适应和扩展,用于变量解释.
主要成果:
- 在常用的序列变异分析资源中确定一系列潜在的陷.
- 一个拟议的修改的人类错误的理性模型,适用于遗传变异分析.
- 强调遗传数据库和文献的动态和不断变化的性质.
结论:
- 该研究提供了一个框架,以了解和减轻遗传变体解释中的错误.
- 拟议的模型旨在提高专业能力和标准化变异分析实践.
- 补充了现有的专业标准和对遗传变异解释的建议.
相关概念视频
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
130
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
130
Evolutionary Relationships through Genome Comparisons
5.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.8K
Genome-wide Association Studies-GWAS
13.5K
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...
GWAS does not require the identification of the target gene involved in...
13.5K
Comparing Copy Number Variations and SNPs
17.7K
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%...
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%...
17.7K
Clinical Trials
6.7K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
6.7K
Bias in Epidemiological Studies
291
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
291


