相关实验视频

Updated: Jun 7, 2025

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks

Published on: September 25, 2021

少是多:对于组成的NGS数据来说,相对排名比绝对丰度更有信息性

Xubin Zheng^1,2,3, Nana Jin^1,2, Qiong Wu⁴

¹Guangdong Provincial Clinical Research Center for Geriatrics, Shenzhen Clinical Research Center for Geriatrics, Shenzhen People's Hospital, Luohu District, Shenzhen 518020, China.

Briefings in functional genomics

|November 21, 2024

概括

分析高通量基因表达数据,包括单细胞RNA测序,面临着构成性数据分析的挑战. 本综述探讨了像对对基因表达分析这样的方法,以提高数据质量和预测临床结果.

科学领域:

基因组学和生物信息学
计算生物学计算生物学
文字转录学 (Transcriptomics) 是一个学科.

背景情况:

高通量基因表达数据 (批量和单细胞RNA-seq) 对于理解生物机制,生物标志物和疾病预后至关重要.
现有的数据预处理方法,如规范化和批次校正,不足以应对组合数据分析带来的挑战.
基于基因表达丰富性的量化方法有局限性;专注于基因表达相对顺序 (ROGER) 的合格方法提供了更有信息的见解.

研究的目的:

审查目前的转录组数据分析方法,突出传统方法的局限性.
介绍和讨论对对基因表达分析方法作为ROGER的增强,以改善数据集成.
探索这些先进分析方法在预测临床结果方面的潜力.

主要方法:

对转录组数据分析技术的文献综述.
专注于合格方法,特别是基因表达的相对顺序 (ROGER).
讨论用于样本或特征空间集成的基因表达的对分析方法.

主要成果:

转录组数据的传统量化方法受到组合数据分析约束的限制.
基于ROGER的合格方法提供了比基于丰度的定量化更可靠的生物信息.
基因表达的对分析方法增强了ROGER的有效数据集成.

结论:

需要先进的分析方法来克服转录组数据分析的局限性.
罗杰及其增强,对基因表达的对分析,显示改善数据质量和整合的希望.
这些方法具有很大的潜力,可以从基因表达数据中预测临床结果.

关键词:

组合数据分析数据分析.数据整合数据集成.一对对进行分析.相对的表达,相对的表达.转录组 (transcriptome) 是一个转录组.

更多相关视频

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

相关概念视频

Ranks

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...

Relative Frequency Distribution

Relative Frequency Distribution

A relative frequency distribution is the proportion or fraction of times a value occurs in a data set. To find the relative frequencies, one can divide each frequency by the total number of data points in the sample. It is very similar to a regular frequency distribution, except that instead of reporting how many data values fall in a class, a relative frequency distribution reports the fraction of data values that fall in a class. These fractions or proportions are called relative frequencies...

Spearman's Rank Correlation Test

Spearman's Rank Correlation Test

Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
Spearman's test calculates...

Friedman Two-way Analysis of Variance by Ranks

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...

RNA-seq

RNA-seq

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...

Review and Preview

Review and Preview

In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
Percentiles are a type of fractile that partition data into...