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Question: Custom scoring for subnetworks in BioNet
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gravatar for enricoferrero
17 months ago by
enricoferrero550
United Kingdom
enricoferrero550 wrote:

BioNet seems to require p-values to generate its scores for each node:

library(BioNet)
library(DLBCL)
data(dataLym)

pvals <- cbind(t=dataLym$t.pval, s=dataLym$s.pval)
rownames(pvals) <- dataLym$label
pval <- aggrPvals(pvals, order=2, plot=FALSE)

fb <- fitBumModel(pval, plot=FALSE)
scores <- scoreNodes(subnet, fb, fdr=0.001)
module <- runFastHeinz(subnet, scores)

I'm building a data integration pipeline where p-values and other factors will be integrated into a score that goes from -1 to +1.

Can I use these custom scores directly as argument to runFastHeinz()? Or do I need to convert them to BioNet scores, somehow? The distribution of BioNet scores in this example seems to be much wider than [-1, 1]:

summary(scores)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
 -7.265  -6.946  -6.417  -5.610  -5.152   8.986

I'm also not entirely sure what the + and - sign mean in the BioNet scores: does the sign represents the directionality of the effect (I.e.: positive=activated, negative=inhibited)?

Thank you.

ADD COMMENTlink modified 17 months ago by branislav misovic120 • written 17 months ago by enricoferrero550
1
gravatar for branislav misovic
17 months ago by
Netherlands, Leiden
branislav misovic120 wrote:

hi again ,
    so in your other post i mentioned the  course i attended last year  , check  link
there you can open this  exercise:  and  in pdf they say
"  In input/Heinz Nodes FDR 7e-04.txt the nodes score that were used to generate the
module referred to in the presentation are given. Observe that this time no p-values but
actual scores are used. ...
$ head Heinz_Nodes_FDR_7e-04.txt
#node score1
ENSMUSG00000057003 -5.07238096949341
ENSMUSG00000057000 -5.48958095921254
ENSMUSG00000002010 -4.16253938119165
 ....
To run heinz on input/nodes 7e-4.txt, we omit the parameters -a, -lambda and -FDR.This will take a few minutes.
"
So you can do it for sure ... (I also played with Fchange only  as that was my data)
If you open function scoreNodes  you will see call to

scoreFunction(fb, fdr=0.01)

...  and help for  fdr argument  says :
"... P-values below this threshold are considered to be significant and will score positively, p-values a bove the threshold are supposed to arise from the null model. The FDR can be used to control the size of the maximum scoring subnetwork,"

I just used some cutof and gave positive scores to my Fchanges and  bellow that i gave negative   ...

Maybe you can email the package  authors  the  link of your post and ask for more insight .

Best,

Branko
 

ADD COMMENTlink written 17 months ago by branislav misovic120
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