贝叶斯神经网络用于基因组预测:不确定性量化和SNP解释与SHAP和GWAS
Jin Sun1, Xiaoran Zhang2, Xiaowei You2
1Department of Statistics, School of Science, Yanshan University, Qinhuangdao, 066004, China. sunjinwork@ysu.edu.cn.
概括
这项研究引入了一个新的深度学习框架,用于棉花育种中的基因组预测. 它提高了准确性,并提供不确定性估计,使作物选择更加可靠和高效.
科学领域:
- 植物育种与遗传学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 机器学习在农业中的应用
背景情况:
- 深度学习模型通过捕捉复杂的基因型-表型关系来显示基因组预测的前景.
- 目前在植物育种中深度学习的应用受限于模型的解释性差以及缺乏不确定性量化.
- 准确的基因组预测对于加速作物改进计划至关重要.
研究的目的:
- 开发一个贝叶斯神经网络 (BNNs) 框架与LASSO规范化,用于准确的,不确定性意识的基因组预测.
- 引入GSMeSP解释性工具,整合SHAP和GWAS,以实现生物学上有意义的SNP优先级.
- 在高地棉花 (Gossypium hirsutum) 中应用和验证多特征基因组预测框架.
主要方法:
- 开发了一个贝叶斯神经网络 (BNNs) 框架,将LASSO规范化纳入多特征基因组预测.
- 集成的SHapley添加式扩展 (SHAP) 与全基因组关联研究 (GWAS) 在GSMeSP解释性工具中的信号.
- 将框架应用于1385个高原棉花加入的基因型,其中有超过12,000个SNP用于与纤维相关的特征.
主要成果:
- 该BNNs模型显著优于传统和深度学习基准,预测准确度提高了0.46-47.85%.
- 该框架提供了特征和样本特定的95%可信度间隔,使得可靠的不确定性量化.
- GSMeSP确定了生物学相关的位置,突出显示了D05染色体作为纤维特征相关SNP的热点.
结论:
- 开发的BNNs框架与LASSO规范化和GSMeSP提供了准确,不确定性意识和生物可解释的基因组预测.
- 这种综合方法提高了作物育种中基因组选择的深度学习的透明度和稳定性.
- 这些发现加速了基因组选择,为育种者提供了更知情和可靠的决策工具.
更多相关视频
08:04Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
Published on: June 6, 2025
1.3K
09:33Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens
Published on: August 25, 2023
1.6K
相关概念视频
Genome-wide Association Studies-GWAS
15.3K
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...
GWAS does not require the identification of the target gene involved in...
15.3K
Comparing Copy Number Variations and SNPs
18.6K
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%...
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%...
18.6K
Single Nucleotide Polymorphisms-SNPs
17.9K
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,...
17.9K
Genomics
39.6K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
39.6K
Propagation of Uncertainty from Systematic Error
1.3K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.3K
