Additional file 1:

A Simple Illustration of How the Choice of a Similarity Measure Affects TOM. The TOM measure of interconnectedness is often used to define clusters of highly interconnected genes. Here we use very simple networks to highlight properties of the TOM measure. (a) Computing the topological overlap between genes 1 and 2 when all connection strengths between intermediate genes equal the constant a. (b) The numbers on the edges of the left network are correlations while the numbers on the edges of the networks on the right hand side equal corresponding unsigned adjacencies (upper network) and signed adjacencies (lower network). In a signed network, the topological overlap between genes 1 and 2 is very low because intermediate genes 3 and 4 have negative correlations with gene 1. In contrast, the topological overlap between genes 1 and 2 is high in an unsigned network.

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Additional file 2:

Intramodular Connectivity is Highly Correlated with Module Eigengene Based Connectivity k_ME. For each module from the Zhou et al data, we plot intramodular connectivity (defined using a weighted network with power β = 1) versus module eigengene based connectivity k_ME. We find that the two connectivity measures are highly correlated. A theoretical derivation between network concepts and eigengene based analogs is presented in [32].

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Additional file 3:

Binding Enrichments for Unsigned and Signed Ivanova et al (2006) Networks. This file contains enrichments and corresponding p-vaules for binding from Loh et al (2006), Boyer et al (2007), and Chen et al (2008).

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Additional file 4:

Comparing Gene Rankings to Regulators of Gene Expression. Here we relate different gene rankings to enrichment significance with regard to the following variables (a) histone H3K4 alone versus all others, (b) bivalent H3K4&H3K27 versus all others [49], (c) high CPG class versus all others (i.e. HCG versus ICG and LCG), (d) promoter CPG methylation status [50], (e) Oct 4 complex binding status, (f) cMyc complex binding status. We report results for 3 different gene rankings using the Ivanova data: the black and blue curve represent gene rankings according to and , respectively. The grey curve represents ranking according to a Student T-test of differential expression. Additional File 4 shows that black and blue module genes can have very different enrichment results that tend to be quite different from those of a standard analysis.

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Additional file 5:

Data for Cross-Referencing Module Membership to Epigenetic Regulators. In this Additional File, we merged Additional File 11 (Module Membership k_ME etc in the Ivanova data) with a Table (S4) from [50] that contained promoter CPG methylation and lysine trimethylation data from [49]. This Additional file reports module membership values, histone modifications, promoter CpG Status, and polycomb, Oct4 complex, cMyc complex binding etc. The table reports data regarding genes whose promoters have H3K4me3, H3K27me3, both, or neither histone mark. Further, column Class reports CPG promoter classifications (high HCP, intermediate ICP, or low LCP). The column Methylated reports which genes are known to be methylated (value 1) or unmethylated (0) [50]. For completeness, it also includes information regarding genes bound by Nanog or Oct4 in the proximal promoter (within 10 kb) or bound by Nanog and Oct4 long range (within 500 kb), or bound by Polycomb [5,6].

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Additional file 6:

Binding Enrichments for Unsigned and Signed Zhou et al (2007) Networks. This file contains enrichments and corresponding p-values for binding from Loh et al (2006), Boyer et al (2007), and Chen et al (2008).

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Additional file 7:

Ingenuity Pathway Analysis of the Pluripotency and Differentiation Modules from Zhou et al (2007).

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Additional file 8:

Comparison of Overlap in Ivanova et al and Zhou et al (2007) when Ranking by t-statistic and Connectivity.

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Additional file 9:

Ingenuity Pathway Analysis of Genes Ranked by Connectivity and Differential Expression in Zhou et al (2007).

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Additional file 10:

Understanding Signed Module Membership. Here we visualize the relative position of unsigned and signed similarity modules. We used module eigengene based connectivity, k_ME = cor(x_i, E), to visualize a gene's module membership, focusing on genes located in the signed turquoise or black modules. For any vectors a and b with angle θ between them, their correlation can be interpreted as cor(a, b) = cos(θ). Using this relationship we plotted genes in polar coordinates (radially) relative to the unsigned turquoise module. The figure shows the angle, θ, between the gene's expression profile and the turquoise module eigengene from the unsigned network, indicated by the solid turquoise line. Each gene's radius is defined as the absolute value of its log₂ expression fold change (FC). FC is the ratio between the average expression in the control RNAi samples and the average expression in the Oct4 RNAi knock down samples. For reference the signed turquoise and black module eigengenes are indicated by dashed turquoise and black lines, respectively, and genes are colored by signed module membership. Known ES cell regulators and differentiation markers are labeled. Note that the signed module eigengenes (dashed lines) reflect the relationship within their corresponding modules while the unsigned module eigengene (solid line) reflects the relationship between the two signed modules.

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Additional file 11:

Module Membership and Binding Information in the Signed Ivanova et al (2006) Network. This file contains module membership, k_ME, and binding data from Loh et al (2006), Boyer et al (2007), and Chen et al (2008) for each gene on the microarray.

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Additional file 12:

Module Membership and Binding Information in the Signed Zhou et al (2007) Network. This file contains module membership, k_ME, and binding data from Loh et al (2006), Boyer et al (2007), and Chen et al (2008) for each gene on the microarray.

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