Knowledge graph centered on Weighted Gene Co-expression Network Analysis (Various) with 26 nodes and 99 connections. Top connected: Pekania pennanti, Perymiscus species, small mammals, DNA methylation networks underlying mammalian trai, Peromyscus maniculatus.
Method synopsis
Weighted Gene Co-expression Network Analysis adapted for methylation data to identify co-methylated CpG modules and their associations with phenotypic traits.
Synthesized from method descriptions across 1 paper using this protocol.
Procedure from a recent peer-reviewed implementation
Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — DNA methylation networks underlying mammalian traits (2023), Science. Implementations in other papers (listed below) may differ.
WGCNA co-methylation network analysis
Performed unsupervised weighted correlation network analysis to identify clusters of highly correlated CpGs (co-methylation modules). Used soft-thresholding power selection and hierarchical clustering to define modules.
Quantities: 55 distinct co-methylation modules identified from 14,705 conserved CpGsDuration: Not specifiedConditions: Computational analysis
Equipment: WGCNA software
Module-trait correlation analysis
Calculated correlations between module eigengenes (first principal component of scaled CpGs in each module) and species traits including maximum lifespan, adult weight, age, sex, and mortality risk using Pearson correlation.
Quantities: Analyzed associations with traits across 348 speciesDuration: Not specifiedConditions: Statistical analysis