通过正统的相关性分析在多omics数据中发现稳定的生物标志物
1Department of Computer Science, Aalto University, Espoo, Finland.
PloS one
|September 9, 2024
概括
这项研究介绍了StabilityCCA,这是一种分析多omics数据的新方法. 它有助于确定复杂疾病的关键变量和生物标志物,如炎症性肠病 (IBD).
科学领域:
- 计算生物学是一种计算生物学.
- 生物信息学是一种生物信息学.
- 机器学习 机器学习
背景情况:
- 多学科分析整合了各种生物数据,以更深入地理解.
- 复杂的疾病,如炎症性肠病 (IBD),需要综合的OMICS方法.
- 现有的方法可能无法充分利用异质的多omics数据.
研究的目的:
- 为无监督多视图学习开发一种新的变量选择方法.
- 增强用于复杂疾病研究的多omics数据的分析.
- 为了确定强大的生物标志物,如IBD等疾病.
主要方法:
- 应用稳定性选择到法定相关性分析 (CCA) 用于多视图学习.
- 开发了一种名为 StabilityCCA.的新方法.
- 在模拟和真实多omics数据集上验证的稳定CCA,包括IBD微生物组数据 (元基因组学和代谢学).
主要成果:
- 稳定性CCA有效地识别相关变量并提高选择稳定性.
- 在模拟和真实世界的多omics数据上表现出更好的性能.
- 在一项IBD病例研究中,将关节元基因组学和代谢学结构与疾病联系起来,并确定了潜在的生物标志物.
结论:
- 多视图学习对于多omics数据集成非常有价值.
- 稳定性CCA是复杂疾病中生物标志物发现的强大工具.
- 该方法揭示了多omics数据结构和疾病病理生理学之间的联系.
更多相关视频
07:47Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
Published on: September 15, 2023
1.4K
07:11Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
Published on: November 10, 2023
2.2K
相关概念视频
Correlation of Experimental Data
224
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
224
Coefficient of Correlation
6.1K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
6.1K
Correlations
32.7K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
32.7K
Correlation and Regression
1.2K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
1.2K
Comparing Copy Number Variations and SNPs
17.6K
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%...
17.6K
Correlation
11.7K
In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
11.7K
