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相关概念视频

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
GWAS does not require the identification of the target gene involved in...
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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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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
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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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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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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,...
268

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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在下一代测序数据中,生成类型预测优于用于小变异检测的统计方法.

Brendan O'Fallon1,2, Ashini Bolia1, Jacob Durtschi1,2

  • 1Institute for Research and Innovation, ARUP Labs, Salt Lake City, UT 84108, United States.

Bioinformatics (Oxford, England)
|September 19, 2024
PubMed
概括

一个新的深度生成模型,Jenever,准确地检测整个基因组测序数据中的生殖系变异. 这种先进的方法在敏感度和精度上超过了小变异基因型定型的现有工具,减少了手动审查负担.

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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

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Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity
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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:

  • 检测生殖系变异对基因组学至关重要.
  • 目前的工具面临着全基因组数据中错误阳性结果的挑战.
  • 手动审查变量调用会造成很大的负担.

研究的目的:

  • 为检测生殖系变种引入一种新的深度生成模型.
  • 提高全基因组测序分析的准确性和减少错误阳性.
  • 为现有变异调用器提供更有效的替代方案.

主要方法:

  • 开发了一个基于变压器的编码器和双解码器的深度生成模型.
  • 在37个来自"瓶中的基因组"样本的全基因组序列上训练模型.
  • 实现了模型作为一个名为Jenever的基于Python的命令行工具.

主要成果:

  • 杰尼弗准确地构建了双胞胎生殖系单体类型,具有正确的阶段和基因型.
  • 与FreeBayes,GATK HaplotypeCaller,Clair3和DeepVariant相比显示出更高的整体准确性.
  • 获得了最高的灵敏度,精度和最少的基因型错误的indel变体,以及SNVs的最高F1分数.

结论:

  • 杰尼弗在生殖系变种检测准确度方面取得了重大进展.
  • 深度生成模型方法有效地解决了传统统计方法的局限性.
  • Jenever为分析全基因组测序数据提供了一个强大而准确的工具.