相关实验视频

Updated: Jul 18, 2025

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

单细胞基因表达数据的差异变异性分析

Jiayi Liu^1,2,3, Anat Kreimer^2,3, Wei Vivian Li^4,5

¹Graduate Programs in Molecular Biosciences, Rutgers, The State University of New Jersey, 604 Allison Rd, Piscataway, 08854, NJ, USA.

Briefings in bioinformatics

|August 20, 2023

概括

我们开发了统计管道来分析单细胞RNA测序 (scRNA-seq) 数据中的基因表达变异性. 最好的管道使用简单的正常化,并确定COVID-19和自闭症患者的细胞变异性变化.

科学领域:

基因组学就是基因组学.
计算生物学计算生物学
生物信息学是一种生物信息学.

背景情况:

单细胞RNA测序 (scRNA-seq) 允许在单个细胞水平上进行基因表达分析.
了解转录变异性对于各种生物状态至关重要,但缺乏可靠的统计方法.
现有的方法很难量化和测试细胞群之间的差异变异性.

研究的目的:

在scRNA-seq数据中确定差异变异性分析的最佳统计管道.
为了比较各种规范化,特征选择,维度缩小和可变性计算方法.
建立分析单细胞转录变异性的最佳实践.

主要方法:

为scRNA-seq数据分析提出并评估了12个不同的统计管道.
使用合成scRNA-seq数据集进行管道性能和准确性的基准测试.
采用基于densSNE的距离到集群中子体作为主要的变化度量.

主要成果:

确定了一个高度准确和强大的管道,涉及简单的库大小正常化和保留所有基因.
最优的管道使用基于densSNE的距离来计算可变性.
成功地将验证的管道应用于来自COVID-19和自闭症患者的现实世界scRNA-seq数据集.

结论:

开发的管道提供了一种强大的方法来量化scRNA-seq数据中的差异基因表达变异性.
这种方法成功地确定了COVID-19和自闭症患者队列中的显著细胞变异性变化.
突出了分析转录变异性的潜力,以了解疾病状态和患者分层.

关键词:

数据规范化的数据规范化.差异变化分析的差异性分析.假设测试测试假设测试单细胞基因组学单细胞基因组学

更多相关视频

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Published on: February 25, 2017

相关概念视频

Cell Specific Gene Expression

Cell Specific Gene Expression

Variability: Analysis

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...

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%...