Additional file 2: Figure S1. of A functional genomic model for predicting prognosis in idiopathic pulmonary fibrosis

Detection of gene co-expression modules in training cohort. Gene expression intensities obtained from Exon 1.0 ST Array were normalized. Probe sets were mapped to U133 plus 2.0 Array and filtered as described in Additional file 1. A total of 2,718 unique genes were retained and subjected to R package â Weighted Gene Co-expression Network Analysis (WGCNA)â to identify co-expressed gene modules. A). Optimization and selection of power for adjacency transition of gene-gene correlation matrix (power =7). B). Cluster dendrogram of the gene co-expression modules represented by different colors. Seven gene co-expression modules were detected by hierarchical clustering using dynamic tree cut algorithm integrated in WGCNA with the following parameters: power=7, minModuleSize=120, mergeCutHeight= 0.3. Unclustered genes (genes not correlated with other genes) were collected in Grey module. (PPTX 187 kb)