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相关概念视频

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Comparing Copy Number Variations and SNPs02:26

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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was  generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...
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RNA-seq03:21

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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. 
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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相关实验视频

Updated: Jun 12, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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在单细胞转录基因数据中利用基因相关性.

Kai Silkwood1,2, Emmanuel Dollinger1,2,3, Joshua Gervin1,2

  • 1Center for Complex Biological Systems, University of California, Irvine, Irvine, CA, USA.

BMC bioinformatics
|September 18, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了BigSur,这是一种分析单细胞RNA测序 (scRNAseq) 数据而没有正常化的新方法. BigSur准确地识别了基因相关性,揭示了对基因调节网络和细胞过程的洞察力.

关键词:
基因共同表达网络的基因.基因监管网络 基因监管网络基因基因相关性黑色素瘤是一种黑色素瘤.一个单细胞RNA测序.

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相关实验视频

Last Updated: Jun 12, 2025

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards
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Transcriptome Analysis of Single Cells
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科学领域:

  • 基因组学就是基因组学.
  • 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:

  • 技术噪音是单细胞RNA测序 (scRNAseq) 分析的一个重大挑战.
  • 现有的算法往往缺乏可控制的准确性,并依赖于临时参数.
  • 由于未知的生物变异,很难确定scRNAseq数据的适当零分布.

研究的目的:

  • 开发一个基于统计的算法来分析scRNAseq数据,以提高准确性和更少的参数.
  • 为了应对在技术噪音中识别真正的生物变异的挑战.
  • 为了能够更深入地探索罕见的细胞类型,细胞状态和基因调节网络.

主要方法:

  • 开发了一种分析方法,假设scRNAseq数据包括细胞异质性,转录噪声和Poisson采样错误.
  • 在没有正常化的情况下分析scRNAseq数据,以避免分布倾斜,特别是在稀疏的数据集中.
  • 介绍了BigSur (从非规范化读取的基本信息学和基因统计) 用于特征选择,细胞聚类和基因-基因相关性识别.

主要成果:

  • 在模拟的scRNAseq数据中,BigSur准确地捕获了弱但重要的相关性结构.
  • 对人类黑色素瘤细胞系数据的分析确定了成千上万的基因相关性.
  • 确定基因相关性的聚类揭示了已知的细胞组件和生物过程,表明了新的关系.

结论:

  • 对基因-基因相关性识别的统计基础方法为功能相关的基因调节网络提供了新的见解.
  • BigSur提供了一种强大的方法来分析非规范化scRNAseq数据.
  • 这些发现有助于更深入地了解细胞异质性和生物过程.