Hi All,

I would like to compare miRNA and mRNA sequencing results using Pathview. By default, Pathview uses a KEGG xml file downloaded using the function pathview(). My first problem is how to feed Pathview with a custom pathway (for example a reactome pathway converted into graphNEL object)?

I am using mirIntegrator package, to integrate miRNA interactions into KEGG pathways. mirIntegrator package contains a function keggPathwayGraphs(), which downloads KEGG pathways. Then, these pathways are augmented by integrating miRNA interactions into gene networks. The resulting pathways (augmented pathways) are graphNEL objects, looking as follows:

> augmented_pathways_mmu_04727
$`path:mmu04727`
A graphNEL graph with directed edges
Number of Nodes = 218 
Number of Edges = 748

I could not figure out how to input a graphNEL object made of reactome pathway. This is what I was trying:

    > library(graphite)
    > MouseReactome <- pathways("mmusculus", "reactome")
    > names(MouseReactome)[1:10]
    > trans_path <- MouseReactome[grep("transmission",names(MouseReactome))]
     [1] "3' -UTR-mediated translational regulation"                                   
     [2] "A tetrasaccharide linker sequence is required for GAG synthesis"             
     [3] "A third proteolytic cleavage releases NICD"                                  
     [4] "Abacavir transmembrane transport"                                            
     [5] "Abacavir transport and metabolism"                                           
     [6] "Abasic sugar-phosphate removal via the single-nucleotide replacement pathway"
     [7] "ABC transporters in lipid homeostasis"                                       
     [8] "ABC-family proteins mediated transport"                                      
     [9] "Acetylcholine binding and downstream events"                                 
    [10] "Acetylcholine Neurotransmitter Release Cycle"                                
   > trans_path
Reactome pathways for mmusculus
1 entries, retrieved on 24-04-2017
> trans_path <- trans_path[[1]]
> head(nodes(trans_path))
[1] "A0A087WR33" "A0A0A6YW90" "A0A0G2JEA7" "A0A0G2JFW0" "A0A0N4SWF8" "A0A0R4J239"
> head(edges(trans_path))
         src       dest  direction                                            type
1 A0A087WR33 A0A0G2JFW0 undirected                                         Binding
2 A0A087WR33 A0A140T8S1 undirected                                         Binding
3 A0A087WR33     D3Z685   directed Control(Out: ACTIVATION of BiochemicalReaction)
4 A0A087WR33     D3Z685 undirected                                         Binding
5 A0A087WR33     D3Z6K8   directed Control(Out: ACTIVATION of BiochemicalReaction)
6 A0A087WR33     D3Z6K8 undirected 
    > trans_path
    "Neurotransmitter receptors and postsynaptic signal transmission" pathway
    Native ID           = R-MMU-112314
    Database            = Reactome
    Species             = mmusculus
    Type of identifiers = UNIPROT
    Number of nodes     = 175
    Number of edges     = 1600
    Retrieved on        = 24-04-2017
    # creating a GRAPHnel object of the pathway; these gives an error with mirIntegrator
    > trans_path_g <- pathwayGraph(trans_path)
    > trans_path_g
    A graphNEL graph with directed edges
    Number of Nodes = 175 
    Number of Edges = 2068 
    > augmented_pathway <- integrate_mir(trans_path_g, mirTarBase)
    Error in as.list.default(X) : 
      no method for coercing this S4 class to a vector

On the other hand, with a graphNEL object generated using keggPathwayGraphs() everything seems to be working fine:

> kegg_pathways_mmu_04727
$`path:mmu04727`
A graphNEL graph with directed edges
Number of Nodes = 88 
Number of Edges = 542 
> augmented_pathways_mmu_04727 <- integrate_mir(kegg_pathways_mmu_04727, mirTarBase)
> augmented_pathways_mmu_04727
$`path:mmu04727`
A graphNEL graph with directed edges
Number of Nodes = 218 
Number of Edges = 748

The second problem is how to use such a custom (augmented) pathway (graphNEL) for visualization using Pathview. What I would like to achieve is a Pathview-rendered visualisation (KEGG or Graphviz) including color-coded fold changes of both, mRNAs (genes) and miRNAs.

Any tips on how this can be achieved I will very, very much appreciate.

Best wishes, Lech