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

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

High-Throughput iNaturalist Image Analysis Reveals Flower Color Divergence in <i>Monarda fistulosa</i>.

The American naturalist·2026
Same author

Evolution of limb and digit identity genes since the tetrapod ancestor.

Nature communications·2026
Same author

Degeneration and adaptive evolution of digits in ratite birds.

Molecular biology and evolution·2026
Same author

Sharkmer: repurposing PCR primers for targeted genome assembly using in silico PCR.

Bioinformatics (Oxford, England)·2026
Same author

T-shaped alignments integrating HIV-1 near full-length genome and partial pol sequences can improve phylogenetic inference of transmission clusters.

PLoS computational biology·2025
Same author

Correction: Zooid arrangement and colony growth in Porpita porpita.

Frontiers in zoology·2025
Same journal

From episodes to populations: evolutionary explanation requires a constructive epistemology.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

Cortical neuron classes and recursive curvature collapse: a neurobiological model of conscious dynamics.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

On model of weight gain of farm animals.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

An investigative network analysis mapping global cancer epidemiology.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

The challenge of distinguishing living from non-living entities.

Theory in biosciences = Theorie in den Biowissenschaften·2026
Same journal

Red fescue (Festuca rubra L.) variety recognition using subset division and neural networks.

Theory in biosciences = Theorie in den Biowissenschaften·2026
查看所有相关文章

相关实验视频

Updated: Jul 11, 2025

Counting Proteins in Single Cells with Addressable Droplet Microarrays
12:25

Counting Proteins in Single Cells with Addressable Droplet Microarrays

Published on: July 6, 2018

8.6K

规范化不需要成为常态:基于计数的数学分析单细胞数据.

Samuel H Church1, Jasmine L Mah2, Günter Wagner2,3,4,5

  • 1Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA. samuelhchurch@gmail.com.

Theory in biosciences = Theorie in den Biowissenschaften
|November 10, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的方法,通过绕过规范化和转换来分析单细胞RNA测序 (scRNA-seq) 数据. 这种方法保留了生物数据的计数性质,提供了更简单,更直观的基因表达比较.

更多相关视频

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
09:57

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

13.0K
Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
11:01

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Published on: November 17, 2016

47.2K

相关实验视频

Last Updated: Jul 11, 2025

Counting Proteins in Single Cells with Addressable Droplet Microarrays
12:25

Counting Proteins in Single Cells with Addressable Droplet Microarrays

Published on: July 6, 2018

8.6K
Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
09:57

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Published on: December 16, 2014

13.0K
Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins
11:01

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

Published on: November 17, 2016

47.2K

科学领域:

  • 分子生物学分子生物学
  • 生物信息学是一种生物信息学.
  • 计算生物学 计算生物学

背景情况:

  • 单细胞RNA测序 (scRNA-seq) 对于识别细胞类型和差异性基因表达至关重要.
  • 当前的工作流程通常会将序列深度正常化,将计数转换为比例丰度.
  • 人们担心这些转换会扭曲scRNA-seq数据,阻碍分析和解释.

研究的目的:

  • 开发一种用于scRNA-seq数据分析的替代方法,避免正常化和转换.
  • 为了保持scRNA-seq数据固有的计数性质,以便进行更准确的比较.
  • 为分析基因表达提供一种更简单,更直观的方法.

主要方法:

  • 避免了scRNA-seq计数数据的正常化和转换.
  • 利用受限制的代数,以测量和抽象代数为基础,来比较细胞.
  • 在基因表达分析中采用诸如点积的基本运算.

主要成果:

  • 证明受限代数足以进行基因表达的有意义比较.
  • 展示了这种方法可以规避与数据转换相关的常见问题.
  • 在Python和R中开发了"countland"包来实现该方法.

结论:

  • 拟议的方法提供了一个比传统的scRNA-seq数据处理更简单,更直观,更少扭曲的替代方案.
  • 通过限制代数来保存数据的计数性质,可以进行强大的基因表达比较.
  • "countland"包为实施这种新的分析策略提供了一个实际的工具.