Arabidopsis gene co-expression network (AGCN) and its functional modules

AGCN

Link

Description

Network

In this file, each line comprises of a pair of Arabidopsis probe sets and the Pearson correlation coefficient (Pcc) between these two probe sets (Pcc > 0.75)

Hub genes

The top 382 nodes (i.e. probe sets) with respect to the node degree formed a clique structure. The directory includes:

·         the probe set identifiers of these 382 nodes.

·         GO enrichment analysis result generated by BiNGO

·         Gene lists (non-overlapping) for over-represented biological process GO terms

Network clustering results

Use MCL algorithm to partition AGCN into modules (i.e. clusters). The directory includes:

·         the clustering result with the inflation parameter (I) set at 1.8.

·         the clustering result with the inflation parameter set at 3.0.

 

Module annotation

GO and pathway term enrichment analysis result for each module using BiNGO. The directory includes:

·         annotations of modules extracted with I = 1.8 (Go terms and pathway terms)

·         annotations of modules extracted with I = 3.0 (GO terms)

Summary of the module annotation

The directory includes:

·         The excel file lists all modules (I = 1.8) which were detected with significantly enriched biological process GO terms. (1) The table lists the modules, the most significantly enriched GO term for the module, the manual annotation of the module. (2) A pie chart was created based on the manual annotations of the modules

·         The excel file lists all significantly enriched GO terms for each module

Module 1

The directory includes:

·         Gene lists (non-overlapping) for 7 major over-represented biological process GO terms

·         Cellular component GO term analysis

Module 4

The directory includes:

·         Gene lists (non-overlapping) for 3 major over-represented biological process GO terms

Module 67

The directory includes:

·         Gene list for the module

 

The random network #1

Link

Description

Random Network

The random network, which assumed the same node degree distribution as the AGCN, was generated using the randomNodeGraph function in the R package graph (version 1.15.6).

Network clustering results

Use MCL algorithm to partition the random network into modules (i.e. clusters). Here, the inflation parameter (I) was set at 1.8.

 

Module annotation

GO enrichment analysis result for each module extracted using I = 1.8

 

The random network #2

Link

Description

Random Network

The random network, which assumed the same node degree distribution as the AGCN, was generated using the randomNodeGraph function in the R package graph (version 1.15.6).

Network clustering results

Use MCL algorithm to partition the random network into modules (i.e. clusters). Here, the inflation parameter (I) was set at 1.8.

 

Module annotation

GO enrichment analysis result for each module extracted using I = 1.8

 

The random network #3

Link

Description

Random Network

The random network, which assumed the same node degree distribution as the AGCN, was generated using the randomNodeGraph function in the R package graph (version 1.15.6).

Network clustering results

Use MCL algorithm to partition the random network into modules (i.e. clusters). Here, the inflation parameter (I) was set at 1.8.

 

Module annotation

GO enrichment analysis result for each module extracted using I = 1.8

 

 

The GGM network 1

Link

Description

Network

The content of the network can be accessed from the supplementary material of (1).

Network clustering results

Use MCL algorithm to partition the GGM network into modules (i.e. clusters). Here, the inflation parameter (I) was set at 1.8.

 

Module annotation

GO enrichment analysis result for each module extracted using I = 1.8

 

 

Cold stress network

Link

Description

Network

The network was constructed from cold stress time course experiment (14 chips).

Network clustering results

Use MCL algorithm to partition the network into modules (i.e. clusters). Here, the inflation parameter (I) was set at 1.8.

 

Module annotation

GO enrichment analysis result for each module extracted using I = 1.8

 

 

1.                  Ma S, Gong Q, Bohnert HJ: An Arabidopsis gene network based on the graphical Gaussian model. Genome Res 2007, 17(11):1614-1625.