![]() Furthermore, the corresponding genes are often spread across different chromosomes with no known connection to one another, hindering understanding of the molecular mechanisms. However, GWAS findings explain only a fraction of heritability. Genome-wide association studies (GWAS) have significantly advanced our understanding of complex phenotypes by identifying disease- and trait-associated genetic markers and suggesting corresponding genes. Our results highlight gaps in our current knowledge of genetics and molecular mechanisms of complex phenotypes and suggest priorities for future GWASs. We present a general-purpose method for estimating and comparing the coherence of molecular-interaction gene networks that accounts for the network size and shape differences. We demonstrate that coherence and modularity measures capture distinct network properties. Metabolic traits and diseases were the most coherent, while psychiatric disorders and intelligence-related traits were the least coherent. We observed a range of coherence estimates for each category of phenotypes. Using STRING and BioGrid PPI databases, we compared the coherence of 116 phenotype-associated gene sets from GWAScatalog against size-matched KEGG pathways (the reference for high coherence) and random networks (the lower limit of coherence). We present a novel method for normalizing the coherence estimates, making them directly comparable. ![]() The internal degree distribution is defined by interaction counts within a phenotype-specific gene network, while the external degree distribution counts interactions with other genes in the whole protein–protein interaction (PPI) network. We introduce a metric for measuring coherence of molecular-interaction networks as a slope of internal versus external distributions of the degree of interactions. However, direct comparison of the degree of interactions is difficult due to different sizes and configurations of phenotype-associated gene networks. Comparing the degree of interactions may help to better understand the coherence of phenotype-specific molecular mechanisms and the potential for therapeutic intervention. High/low degree of interactions is suggestive of coherent/random molecular mechanisms, respectively. Phenotypes such as height and intelligence, are thought to be a product of the collective effects of multiple phenotype-associated genes and interactions among their protein products.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |