集群DE:一种集群后差异表达 (DE) 方法,它对由双浸泡引起的虚假正值通货膨胀具有稳定性
Dongyuan Song1, Kexin Li2, Xinzhou Ge2
1Bioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, CA 90095-7246.
Research square
|August 14, 2023
概括
拟议的ClusterDE方法解决了单细胞RNA测序分析中的"双浸"问题. 它通过生成合成零数据来控制细胞类型标记基因的错误发现,提高scRNA-seq和多omics研究的准确性.
科学领域:
- 计算生物学 计算生物学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 标准的单细胞RNA测序 (scRNA-seq) 分析涉及细胞类型识别的聚类,然后进行差异表达 (DE) 测试.
- 这种共同的方法受到了损害.
- 双倍的浸泡方式
- ,其中相同的数据用于聚类和DE基因识别,为细胞类型标记基因增加了假阳性.
结论:
- 在scRNA-seq数据分析中,ClusterDE为准确的细胞类型标记基因发现提供了可靠的解决方案.
- 它的适用性超越scrRNA-seq,扩展到其他聚类后的DE分析,包括单细胞多组数据.
相关概念视频
01:20Cluster Sampling Method
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
01:10Bonferroni Test
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...