Skip to main content
Fig. 2 | BMC Genomics

Fig. 2

From: Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle

Fig. 2

The weighted gene correlation network analysis (WGCNA) for 24 RNA-Seq datasets. a 16 gene modules generated from WGCNA analysis. b Gene modules associated with four physiological stages (Post-partum Healthy, H_Post; Pre-partum Healthy, H_Pre; Post-partum Ketosis, K_Post; Pre-partum Ketosis, K_Pre) and seven blood bio-indicators (TC: total cholesterol, TG: total triglyceride, HDL: high-density lipoprotein, LDL: low-density lipoprotein, Ca: calcium, INS: insulin, BHBA: beta-hydroxybutyrate). The statistical significance of module-trait relationship is corrected for multiple testing using the FDR method, where “*” and “.” are for FDR < 0.05, < 0.1, respectively. The values in the brackets are the numbers of genes in corresponding modules. c The top significantly enriched biological processes for genes in the top four modules associated with the K_Post group. d The top significantly enriched tissue/cell types for genes in the top four modules associated with the K_Post group

Back to article page

BMC Genomics

ISSN: 1471-2164

Contact us