Dear List,

 I have recently started exploring the Package ‘BioNet’ for network analysis of microarray data. I have a fundamental question about the interpretation of the results. From my understanding, BioNet first takes a series of p-values, fits them to a model, and then uses this information to score the nodes of a given network (the package is based on a human protein-protein interaction network) and output the best scoring subnetwork. In the 2D visualization of this subnetwork, squares represent nodes with a negative score and circles represent nodes with a positive score. What I do not understand is what the sign of the scores represents, i.e., what is the interpretation of an interaction between two positive nodes vs the interaction of two negative nodes? 

 I am attaching the code from the BioNet Tutorial for the introductory example, only I am not aggregating the pvalues, but rather just taking the pvalues for differential expression (because I am only using this information for my own data). I also changed the FDR threshold so that the resulting network would be smaller.

Thanks a lot in advance.

 

Best,

 

  Eva

----------
Eva Benito Garagorri
PhD program in Neurosciences
Institute for Neurosciences in Alicante
UMH-CSIC
San Juan de Alicante
03550
Spain
ebenito@umh.es
(34) 965 91 92 33

 

----------------

library(BioNet)

library(DLBCL)

data(dataLym)

data(interactome)

pvals=dataLym$t.pval

names(pvals)=dataLym$label

subnet=subNetwork(dataLym$label,interactome)

subnet=rmSelfLoops(subnet)

fb=fitBumModel(pvals,plot=FALSE)

scores=scoreNodes(subnet,fb,fdr=0.000001)

module=runFastHeinz(subnet,scores)

logFC=dataLym$diff

names(logFC)=dataLym$label

plotModule(module,scores=scores,diff.expr=logFC)

----------

> sessionInfo()

R version 2.11.1 (2010-05-31)

x86_64-apple-darwin9.8.0

 

locale:

[1] es_ES.UTF-8/es_ES.UTF-8/C/C/es_ES.UTF-8/es_ES.UTF-8

 

attached base packages:

[1] stats     graphics  grDevices utils     datasets  methods   base    

 

other attached packages:

[1] DLBCL_1.2     BioNet_1.6.5  RBGL_1.24.0   graph_1.26.0  Biobase_2.8.0

 

loaded via a namespace (and not attached):

[1] AnnotationDbi_1.10.2 DBI_0.2-5            igraph_0.5.4       

[4] RSQLite_0.9-2        tools_2.11.1         XML_3.1-0           

>

 

 

 

 

 
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