.png){kind=icon}
返回
Inferring sparse structure in genotype-phenotype maps
.png){kind=icon}
OA
AI
DOI：10.1093/genetics/iyad127.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Correlation among multiple phenotypes across related individuals may reflect some pattern of shared genetic architecture: individual genetic loci affect multiple phenotypes (an effect known as pleiotropy), creating observable relationships between phenotypes. A natural hypothesis is that pleiotropic effects reflect a relatively small set of common core cellular processes: each genetic locus affects one or a few core processes, and these core processes in turn determine the observed phenotypes. Here, we propose a method to infer such structure in genotype-phenotype data. Our approach, sparse structure discovery (SSD) is based on a penalized matrix decomposition designed to identify latent structure that is low-dimensional (many fewer core processes than phenotypes and genetic loci), locus-sparse (each locus affects few core processes), and/or phenotype-sparse (each phenotype is influenced by few core processes). Our use of sparsity as a guide in the matrix decomposition is motivated by the results of a novel empirical test indicating evidence of sparse structure in several recent genotype-phenotype datasets. First, we use synthetic data to show that our SSD approach can accurately recover core processes if each genetic locus affects few core processes or if each phenotype is affected by few core processes. Next, we apply the method to three datasets spanning adaptive mutations in yeast, genotoxin robustness assay in human cell lines, and genetic loci identified from a yeast cross, and evaluate the biological plausibility of the core process identified. More generally, we propose sparsity as a guiding prior for resolving latent structure in empirical genotype-phenotype maps.
Keyword:
genotype-phenotype map
penalized matrix decomposition
structure discovery
sparsity
期刊
IF:
5.1
论文数:
8.2K
被引数:
3.6W
机构
引用论文
Fitness variation across subtle environmental perturbations reveals local modularity and global pleiotropy of adaptation.png)
ELIFE
OAAI
ELIFEIF0
OAAI分享收藏Apparent latent structure within the UK Biobank sample has implications for epidemiological analysisNATURE COMMUNICATIONSOAAI
NATURE COMMUNICATIONSIF15.7
OAAI分享收藏分享收藏The pleiotropic structure of the genotype-phenotype map: the evolvability of complex organisms基因型-表型图的多效性结构: 复杂生物的可进化性
PREAI
分享收藏Saccharomyces Genome Database: the genomics resource of budding yeastNUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏
查看更多内容