在关联网络中持续的批量效应的更高阶校正
Soel Micheletti1, Daniel Schlauch1,2,3, John Quackenbush1,2,4
1Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Bioinformatics (Oxford, England)
|September 3, 2024
概括
批量效应可以在基因共同表达网络中创建错误的关联,即使在标准校正后. 我们介绍了COBRA,这是一种新的方法,可以准确地调整基因联合表达矩阵,从基因组数据中改善生物见解.
科学领域:
- 基因组学就是基因组学.
- 系统生物学 系统生物学
- 生物信息学是一种生物信息学.
背景情况:
- 系统生物学经常从基因表达数据中推断基因共同表达网络,以确定功能模块和调节关系.
- 众所周知,批量效应引入系统偏差,混差异基因表达 (DE) 分析,但它们对基因共同表达的影响仍未得到充分研究.
- 标准批量校正方法可以改善DE分析,但不能完全解决虚假差异共同表达 (DC),可能导致人工关联.
研究的目的:
- 调查批量效应对基因共同表达分析的影响.
- 开发一种方法来纠正基因联合表达矩阵中的批量效应.
- 提高基因调控网络推断和功能模块识别的准确性.
主要方法:
- 在使用合成和现实数据进行标准批次校正后,证明了共变性中混杂的持久性.
- 介绍了同表达批量减少调整 (COBRA),这是一种计算批量纠正基因同表达矩阵的方法.
- 科巴估计了一个条件共变矩阵,控制连续和分类共变量.
主要成果:
- 标准批量校正方法不能消除基因共表达共变性中的混因素.
- COBRA有效地计算了批量纠正的基因共同表达矩阵.
- 科巴利用基因组数据的模块化结构进行高效和准确的关联估计.
结论:
- 批量效应显著影响基因共同表达网络,导致错误的生物学关联.
- 在基因共同表达分析中,COBRA为批量效应校正提供了强大的解决方案.
- 这种方法提高了基因调控网络推断和功能基因组学研究的可靠性.
更多相关视频
09:01A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Published on: May 7, 2014
10.2K
08:51Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
5.6K
相关概念视频
01:23Correlation of Experimental Data
227
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,...
227
02:20Correlations
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
01:53Cause and Effect
10.9K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
10.9K
01:15Drug Concentration Versus Time Correlation
678
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
678
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
00:53Correlation 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