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相关概念视频

RNA-seq03:21

RNA-seq

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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...
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相关实验视频

Updated: Jul 1, 2025

2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications
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2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications

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使用数据转换和矩阵变异高斯混合模型进行三向RNA测序数据的集群程序.

Theresa Scharl1, Bettina Grün2

  • 1Institute of Statistics, University of Natural Resources and Life Sciences, Vienna, Austria. theresa.scharl@boku.ac.at.

BMC bioinformatics
|March 1, 2024
PubMed
概括

我们介绍了一种新的方法,用于聚类三向RNA测序 (RNA-seq) 数量数据,将其视为组成数据. 这种方法增强了对基因表达模式的分析随着时间的推移和跨生物复制品.

关键词:
组合数据是指组成的数据.斯混合物 斯混合物基因表达 基因表达 基因表达基因组学就是基因组学.基于模型的聚类.

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Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
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Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing In Vitro and in Cells
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相关实验视频

Last Updated: Jul 1, 2025

2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications
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科学领域:

  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学
  • 基因组学就是基因组学.

背景情况:

  • RNA测序 (RNA-seq) 时间过程实验产生复杂的三向计数数据 (基因,时间点,生物单位).
  • 聚类RNA-seq数据对于识别随着时间的推移共同表达的基因至关重要.
  • 规范化的RNA-seq计数表现出组合数据特性,需要专门的分析方法.

研究的目的:

  • 开发和验证一个强大的程序,用于聚类三向RNA-seq计数数据.
  • 通过时间和生物变异有效分析基因表达特征.
  • 改进生物相关基因表达模式的提取.

主要方法:

  • 预处理RNA-seq数据以获得正常化表达形状.
  • 应用加法日志比率 (CLR) 变换来将组成数据转换为欧几里德向量.
  • 使用矩阵变量高斯混合模型来集群转换的数据.
  • 通过基于密度的轮信息和可视化的集群地图来评估集群质量.

主要成果:

  • 拟议的方法成功地聚合了三向RNA-seq数据,考虑到其组成性质.
  • 评估指标表明有效的集群分离和紧性.
  • 该程序使用裂变酵母的RNA-seq数据进行了说明,显示了与双向方法相似的结果.

结论:

  • 开发的程序提供了一个合适的方法,用于聚类三向RNA-seq数据.
  • 组合数据分析技术,如CLR转换,对于RNA-seq数据是有益的.
  • 这种方法增强了对复杂实验设计中的基因共同表达动态的理解.