Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

RNA-seq03:21

RNA-seq

11.8K
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...
11.8K
Cluster Sampling Method01:20

Cluster Sampling Method

14.0K
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...
14.0K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

BayesRare: Bayesian mixture model for population-level rare cell type detection in multi-subject single-cell RNA sequencing data.

Briefings in bioinformatics·2026
Same author

Revealing the Best Strategies for Rare Cell Type Detection in Multi-Sample Single-Cell Datasets.

Genes·2026
Same author

Who is using AI to code? Global diffusion and impact of generative AI.

Science (New York, N.Y.)·2026
Same author

Lactylation in Cancer: Unlocking the Key to Drug Resistance and Therapeutic Breakthroughs.

Oncology research·2025
Same author

Efficacy of gut microbiota-based therapy for autism Spectrum Disorder and attention Deficit Hyperactivity Disorder: a systematic review and meta-analysis.

Psychology, health & medicine·2025
Same author

Ultra-low-dose hepatic computed tomography with a novel real-time deep learning-based noise reduction algorithm: a prospective cross-sectional analysis of image quality and lesion detection.

Quantitative imaging in medicine and surgery·2025

相关实验视频

Updated: Jan 16, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

657

空间意识调整的Rand指数用于评估空间转录学集群.

Yinqiao Yan1, Xiangnan Feng2, Xiangyu Luo3

  • 1School of Mathematics, Statistics and Mechanics, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing 100124, China.

Biometrics
|September 26, 2025
PubMed
概括

我们介绍了空间意识的兰德指数 (spRI) 和spARI,以更好地评估空间转录组学集群. 这些指标包括空间距离,比ARI等传统方法提高了准确性.

关键词:
兰德指数 兰德指数 兰德指数集群评估评估的聚类.超几何分布的超几何分布空间转录学 空间转录学

更多相关视频

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.4K
Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis
07:40

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

901

相关实验视频

Last Updated: Jan 16, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

657
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.4K
Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis
07:40

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

901

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:

  • 空间转录学 (ST) 聚类对于理解组织异质性至关重要.
  • 精确的ST聚类可以提高下游的生物分析.
  • 目前的基准测试方法缺乏空间意识.

研究的目的:

  • 提出新的指标,spRI和spARI,用于评估ST集群.
  • 为了解决空间数据中调整后的兰德指数 (ARI) 的局限性.

主要方法:

  • 开发了具有空间意识的兰德指数 (spRI),结合了对象距离.
  • 引入了空间意识调整的兰德指数 (spARI),对随机机会进行了调整.
  • 使用模拟研究和真实ST数据集评估指标.

主要成果:

  • spRI和spARI有效地结合了空间距离信息.
  • 拟议的指标有利于聚类中的空间连贯性.
  • 在评估ST集群方法方面,spARI显示了比ARI更好的实用性.

结论:

  • spRI和spARI提供了更准确的空间ST集群评估.
  • 这些指标提供了比ARI更好的空间连贯性评估.
  • 拟议的方法提高了ST集群方法的基准测试.