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相关概念视频

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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RACE - Rapid Amplification of cDNA Ends02:35

RACE - Rapid Amplification of cDNA Ends

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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Introduction to R01:11

Introduction to R

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R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
351
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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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Sanger Sequencing01:57

Sanger Sequencing

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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Genetic Variation01:25

Genetic Variation

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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...
297

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ShinyCore:一个R/Shiny程序,用于建立基于单核酸多态数据的核心收集.

Steven Kim1, Dong Sub Kim2, Hana Moyle1,3

  • 1Department of Mathematics and Statistics, California State University, Monterey Bay, Seaside, USA.

Plant methods
|October 11, 2023
PubMed
概括

ShinyCore是一种选择核心收藏的新方法,增强遗传多样性并改进数据管理. 与现有的算法相比,这种用户友好的工具为大型数据集提供了更快的处理速度.

关键词:
核心集合 核心集合 核心集合评估指标评估指标细菌体细胞质的发生.在R/Shiny中使用.单个核酸的多态性.

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科学领域:

  • 植物育种 植物育种
  • 遗传学 遗传学 是一个
  • 生物信息学是一种生物信息学.

背景情况:

  • 管理大量的遗传资源是复杂的.
  • 核心收藏提供了一个代表性的研究和育种子集.
  • 有效的核心收藏需要高的遗传多样性和最小的冗余.

研究的目的:

  • 介绍ShinyCore,这是一种用于核心集合选择的新双相方法.
  • 改进现有的核心集合管理算法.
  • 提高遗传多样性和数据处理效率.

主要方法:

  • ShinyCore采用了两阶段的方法:覆盖标准,然后是稀有性得分.
  • 覆盖标准很快就建立了一个定义的遗传代表水平.
  • 稀有度得分优先考虑独特的等位基因以最大限度地提高多样性.

主要成果:

  • ShinyCore比GenoCore更快地实现了用户定义的覆盖范围,特别是对于大型数据集.
  • 稀有性得分有效地提高了遗传多样性和距离指标.
  • ShinyCore展示了卓越的速度和多样性增强能力.

结论:

  • ShinyCore为核心收集选择提供了一个可访问和高效的替代方案.
  • 该方法很容易通过RStudio实现,并提供交互式Web应用程序.
  • ShinyCore有利于研究人员和育种人员,特别是那些与大型遗传数据集工作的人.