Re: [igraph] Extracting subnets automatically for further analysis based on metric scores

[Gábor Csárdi]

Hi Alex,

you can use the induced.subgraph() function with symbolic names. E.g. here is an example with a random graph where we pick out the subgraph including the top 10 nodes according to their page rank:

g <- erdos.renyi.game(26, 5/26)

V(g)$name <- letters

pr <- page.rank(g)$vector

top10 <- pr[order(pr, decreasing=TRUE)[1:10]]

subnet <- induced.subgraph(g, names(top10))

subnet

# IGRAPH UN-- 10 14 -- Erdos renyi (gnp) graph

# + attr: name (g/c), type (g/c), loops (g/l), p (g/n), name (v/c)

I hope this helps,

Gabor

On Thu, Mar 7, 2013 at 6:03 PM, Alex Upton <address@hidden> wrote:

Hello all,

I have a query I hope that you could help me with. After creating my network, and calculating a number of metrics, I would then like to automatically extract the subnets of the nodes with the 10 lowest ranks for each ( I have ranked the nodes with the highest scores 1, so would like those nodes from 1 to 10).  This has been done as such:


wdrank1 <- rank(-wd1s)
brank1 <- rank(-wb1s)
crank1 <- rank(-c1s)
hrank1 <- rank(-h1s)
erank1 <- rank(-e1s)
lrank1 <- rank(-l1s)
drank1 <- rank(-d1s)


The names for these nodes are gene symbols, and the output of each of these objects is the list of all the genes with their ranks for that category.

Previously I have used a crude approach to extract the subnets; seeing which gene symbols are the top ten, and then doing a bit of trial and error to find the node numerical ID that matches the gene symbol. What I would like is to take the top 10 gene symbols for each category, and then create the subnets for these 10 gene symbols automatically. Then, it would be helpful to output this to an edgelist with the nodes as gene symbols and not node numerical IDs, so that these lists can then be fed to a program for gene set enrichment analysis. Is there a way then that I can do this? Any help would be greatly appreciated.

Kind regards,

Alex

--------------------------------------------------------------------------------------------
Alex Upton, BEng, MRes, PG Cert Business Administration

PhD Researcher Biomedical Informatics, Signals and Systems
School of Electronic, Electrical and Computer Engineering,
College of Engineering and Physical Sciences, University of Birmingham
Edgbaston, Birmingham, B15 2TT, United Kingdom

Fax: +44 121 4144291 (school general office)
Email: address@hidden

Personal Web: http://postgrad.eee.bham.ac.uk/uptona/
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Gabor Csardi <address@hidden>     MTA KFKI RMKI