Hierarchical clustering of the enriched pathways.

<p>Each cluster is encircled by a rectangle and numbered. Clustering coefficient of common module in each cluster is shown in parentheses. None: represent the fact that there are no common associated genes within the corresponding cluster.</p

List of selected gene expression data sets.

<p>^a: The number of significantly differentially expressed genes.</p><p>List of selected gene expression data sets.</p

Subclasses of enriched KEGG pathways.

<p>The number of pathways belong to each subclass is shown in parentheses. Pathways mentioned in section 3.2 are labeled. ^a: Benjamini and Hochberg adjusted p-value; ^b and ^c: Number and percentage of associated genes in each pathway. Percentage represents the proportion of associated genes in all known genes involved in a pathway.</p

Workflow for identification of shared pathways and common modules among AD, PD and HD.

<p>In the first step, AD, PD and HD susceptibility gene (sg) sets were collected and their intersection were defined as common sg. Meanwhile, common sg's first neighbors in the human protein-protein interaction network (hPPIN) was extracted to construct common gene first neighbor network (CFNN). Then, KEGG pathway enrichment analysis was applied to the nodes in CFNN to get shared pathways of AD, PD and HD, following by gene expression analysis to evaluate the found pathways. Finally, hierarchal clustering was applied to cluster the enriched pathways and indentify common modules in CFNN. RWR: random walk with restart.</p

Probability density for obtaining common genes.

<p>The observed value is marked with a filled triangle.</p

Probability density for obtaining the number of components in adherens and tight junction pathways.

<p>(A) and (C) for PD, (B) and (D) for AD; the observed value is marked with a filled triangle.</p

The common module from cluster 2.

<p>Their relationship with common susceptibility genes of AD, PD and HD is depicted. Module inner interactions are labeled by solid line, its relationship with susceptibility genes by dashed line. Gene names are marked on the nodes. ¹: pathways related to inflammation, ²: pathways involved in infectious diseases.</p

Pathway clustering analysis and common module extracting.

<p>(A) Diagram of clustering analysis. Hierarchical clustering was applied and only associated genes in a specific pathways were considered, not the full genes. (B) Extracting common module from a pathway cluster. The common module is a part of CFNN, and might playing a bridging role in linking enriched pathways and neurodegeneration.</p