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

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


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]:

   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 15 months ago by branislav misovic120 • written 15 months ago by enricoferrero550
gravatar for branislav misovic
15 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 .



ADD COMMENTlink written 15 months ago by branislav misovic120
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