I am not sure what you are trying to do here. Can you give a small example
with the output you expect? Please also see
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example

Gabor

On Fri, Feb 6, 2015 at 9:55 AM, Benika H <[email protected]> wrote:

> Hi everyone,
>
> I have a list of seed nodes in a file like such :    hsa-let-7f-2
> hsa-let-7f-2  hsa-let-7f-2  hsa-let-7f-2  hsa-mir-106b  hsa-mir-1180
> hsa-mir-1228
>  hsa-mir-1248  hsa-mir-1248
> and I have my edgelist that looks like this:
>   MCCC1 MCCC2  MCCC2 AUH  MCEE MUT  MCEE PCCA  MCF2 CAP1  hsa-mir-1228
> COG8  MCF2 COPA  MCF2 COPB2  MCF2 DOCK2  MCF2 GNA13  MCF2 GNG2
> I want to find the communities that holds my seed nodes with at most 8 of
> its closest interactions.
>
> I've tried the following lines:
> genes <- read.table("~/Desktop/connected.txt", header=FALSE, sep="\t")
> g=as.matrix(genes)
>
> y <- graph.edgelist(g, directed=FALSE)
>
> seeds <- read.table("~/Desktop/combined.txt", header=TRUE, sep="\t")
> seeds <- as.data.frame(sedds)
> seeds <- seeds$seednodes
>
> x <- which(farthest.nodes(g) %in% communities(sg) <= 9)
> subg <- induced.subgraph
> (graph=y,vids=unlist(neighborhood(graph=y,order=9,nodes=seednodes)))
>
> Both of these give me 3 communities and only one contains one of my seed
> nodes, but when I look at the communities using communities(sg), I see more
> than that.
>
> Any help would be greatly appreciated.
>
>
>
> Beni H
>
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>
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