Fig. 2

CGSA bioinformatic pipeline overview. a Systems biology approach to improve identification and annotation of the Acute SIV Co-Expression Network in acute SIV infection data. (Lower path) GO enrichment analysis of the 7420 DE genes was used to identify biological function relevant for acute SIV infection in AGMs and RMs. Twenty-three reference datasets pertaining to relevant processes were collected and used to improve the biological support and annotate the Acute SIV Co-Expression Network. (Upper path) A co-expression network was first constructed from acute SIV infection data. Each interaction was then weighted based on correlations in reference datasets. The network was then partitioned into modules that underwent annotation based on reference datasets. b The Acute SIV Co-Expression Network, in which the resulting modules were connected to the two modules with which it shared the highest number of interactions. Each pie chart shows the ratio of up (orange) and down (blue) regulated genes at each time point in each SIV host species. Concentric circles mark 20% of the total number of genes in each module. Node sizes represent numbers of genes in each module. Interaction thickness represent the number of interactions between each module. c Summary of functional enrichment tests for each network module. d Whole-genome correlation between acute SIV infection and reference datasets. Colors in heatmaps represent the Pearson correlation coefficient between logFC values in acute SIV infection and the reference dataset specified. In wound healing, two points from the time series, 24 h and day 7, are shown. In cytokine stimulation, 12 h (interferons) or 6 h (TNF-α) data are shown. In colitis and microbial colonization, day 7 and day 16, respectively, are shown