Use of Viper with a regulatory network built with my dataset or another one?
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ldetorrente ▴ 10
@ldetorrente-10730
Last seen 7.9 years ago

Hi,

I am trying to use the viper package and having trouble figuring out which regulatory network I should use. Should I build one with aracne-ap directly on my dataset or better to use one from another dataset?

I am working on a breast cancer dataset so my idea was to use viper with the regulatory networks defined in aracne.networks as they were built on TCGA so also cancer related (and even breast cancer related). I have the impression that the example in the vignette  on Human B-cell used the same dataset (dset from the bcellViper package) to built the regulatory networks (regulon from the bcellViper package) but I am not 100% sure, does someone know if it's the case?

Thank you for your help!

> sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.10.5 (Yosemite)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] aracne.networks_0.99.7 bcellViper_1.8.0       viper_1.7.4           
[4] Biobase_2.32.0         BiocGenerics_0.18.0   

loaded via a namespace (and not attached):
[1] MASS_7.3-45        class_7.3-14       tools_3.3.1        mixtools_1.0.4    
[5] KernSmooth_2.23-15 segmented_0.5-1.4  e1071_1.6-7        boot_1.3-18      

 

 

 

 

viper aracne regulatory network aracne.networks • 1.2k views
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Entering edit mode
ldetorrente ▴ 10
@ldetorrente-10730
Last seen 7.9 years ago

The maintainer of the package (Mariano J Alvarez) was actually very fast at answering emails. As maybe other people are wondering I will copy paste his answer here and hope it helps other!

I would definitely use the BRCA network from aracne.networks package (bioconductor). The network should be tissue-matched to the gene expression signatures you want to analyze, but does not need to be generated from the same dataset.

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