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

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

4.8K
4.8K

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

Genetic effects put into context.

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

SECmeres outperform extracellular vesicles as potential blood RNA biomarkers for Alzheimer's disease.

Nature communications·2026
Same author

Transcriptome-wide association studies implicate RCC1 and PHACTR4 in prostate cancer survival.

European journal of human genetics : EJHG·2026
Same author

Optimal gene panel selection for targeted spatial transcriptomics experiments.

Nucleic acids research·2026
Same author

Combinatorial effects of gene dosage, polygenic background and environment on complex traits.

medRxiv : the preprint server for health sciences·2026
Same author

GROMTools: scalable individual-level GReX imputation for mega-biobank-scale cohorts.

medRxiv : the preprint server for health sciences·2026
Same journal

A unified analysis of cell type- and trajectory-associated pathways in single-cell data using Phoenix.

Genome research·2026
Same journal

Resf1 is required for proper placental development and configuration of trophoblast cell-specific heterochromatin.

Genome research·2026
Same journal

Telomere-driven replicative crisis is driven by large-scale changes in genomic architecture.

Genome research·2026
Same journal

Spatially informed reference-free cell-type deconvolution for spatial transcriptomics with SpatialCD.

Genome research·2026
Same journal

Spatially resolved profiling of steroid nuclear receptors reveals a role for the disordered N-terminal domains in genome targeting and AP-1 interaction.

Genome research·2026
Same journal

Flexible and scalable inference of spatially varying correlation in spatial transcriptomics with spCorr.

Genome research·2026
查看所有相关文章

相关实验视频

Updated: Sep 18, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
06:24

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

3.7K

QuadST在空间解析的转录组学数据中识别了细胞与细胞相互作用改变的基因.

Xiaoyu Song1, Yuqing Shang2, Michelle E Ehrlich3

  • 1Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore 169857; song.xiaoyu@duke-nus.edu.sg.

Genome research
|June 23, 2025
PubMed
概括
此摘要是机器生成的。

QuadST是一种新的统计方法,可在空间解析转录学 (SRT) 中稳定识别细胞-细胞相互作用及其受影响的基因. 它通过控制错误和增加疾病研究能力来改进现有方法.

更多相关视频

Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR
09:03

Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR

Published on: May 29, 2014

11.6K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.7K

相关实验视频

Last Updated: Sep 18, 2025

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq
06:24

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

3.7K
Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR
09:03

Profiling Individual Human Embryonic Stem Cells by Quantitative RT-PCR

Published on: May 29, 2014

11.6K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.7K

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:

  • 空间解析的转录学 (SRT) 能够研究细胞与细胞相互作用,这对于了解疾病至关重要.
  • 现有的识别这些相互作用的方法有局限性.

研究的目的:

  • 引入QuadST,一种新的统计方法,可在单细胞SRT中稳定识别细胞-细胞相互作用及其受影响的基因.
  • 为分析空间转录基因数据提供强大而准确的工具.

主要方法:

  • 在不同的距离量度上,QuadST模型的细胞与细胞相互作用.
  • 它对比信号以识别受相互作用影响的基因,优先考虑那些在较短距离有更强信号的基因.
  • 该方法不需要预先指定相互作用的细胞对,并且对混因素和数据错误具有稳定性.

主要成果:

  • 模拟研究表明,QuadST有效地控制了I型错误,即使使用了错误指定的模型.
  • 与现有方法相比,QuadST显著提高了统计能力.
  • 对真实数据集的应用确定了跨多种细胞类型的生物学显著的相互作用-改变基因.

结论:

  • 在SRT中,QuadST提供了一种强大而强大的方法来分析细胞-细胞相互作用.
  • 这种方法通过空间转录组分析增强了参与疾病机制的基因的发现.
  • QuadST在空间生物学和疾病研究领域取得了进展.