对scRNA-seq的多重学习方法进行比较研究,使用轨迹感知度量
Mehdi Nadjafikhah1, Mohammad Nasiri2
1Iran University of Science and Technology, Tehran, Iran.
Scientific reports
|August 7, 2025
概括
本研究将单细胞RNA测序 (scRNA-seq) 数据的维度减小方法进行比较. 一个新的指标,轨迹意识嵌入得分 (TAES),评估集群和发展轨迹的保存.
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:
- 单细胞RNA测序 (scRNA-seq) 显示了细胞的异质性.
- 高维的scRNA-seq数据带来了分析挑战.
- 缩小尺寸对于可视化和解释scRNA-seq数据至关重要.
研究的目的:
- 为了比较四种维度减小技术的性能:PCA,t-SNE,UMAP和扩散地图.
- 为了引入和验证一个新的指标,轨迹意识嵌入得分 (TAES).
- 为scRNA-seq数据分析选择合适方法提供指导.
主要方法:
- 将PCA,t-SNE,UMAP和扩散地图应用于三个基准scRNA-seq数据集 (PBMC3k,胰腺,BAT).
- 开发并使用轨迹意识嵌入得分 (TAES) 进行评估.
- 基于聚类准确性和发展轨迹的保存的评估方法.
主要成果:
- PCA提供快速,线性减少.
- t-SNE和UMAP有效地捕获细胞群.
- 扩散地图擅长揭示连续的发展轨迹.
- 泰斯得分与观察到的集群和轨迹保存相关.
结论:
- 没有任何一种方法对所有scRNA-seq分析目标都是最佳的.
- 选择缩小维度的方法取决于是否优先考虑聚类或轨迹推理.
- TAES为scRNA-seq嵌入提供了一个全面的评估框架.
更多相关视频
07:35Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
Published on: December 1, 2023
771
10:10Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Published on: September 18, 2021
38.5K
相关概念视频
RNA-seq
10.4K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.4K
Improving Translational Accuracy
11.9K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.9K
Ribosome Profiling
3.6K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.6K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
101
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
101
