Table 1

Overview of significance evaluation

1: A = z-transformed phosphoproteomic data (n phosphosites, m replicates)

2: STRING = STRING interaction data

3: origSN = list of extract subnetworks from STRING using A

4: flippedSNs = container for flipped subnetwork lists

5: for all s ∈ Cartesian product {-1, +1}^m without {(-1,...,-1), (+1, ..., +1)} do

6:   flippedA = multiply values in column (1, ..., i, ..., m) of A with the value at index i in s

7:   add list of extracted subnetworks from STRING using flippedA to flippedSNs

8: end for

9: FDR = 1.0

10: N = n

11: while FDR > desired FDR cutoff and N >0 do

12:   origCount = count subnetworks that are among the N most-regulated ones across all replicates in origSN

13:   flippedCount = 0

14:   for all flipped lists of subnetworks in flippedSNs do

15:      flippedCount = flippedCount + number of subnetworks from list of flipped subnetworks that are among the N most-regulated ones across all replicates

16:   end for

17:   FDR = (flippedCount/number of lists in flippedSNs)/origCount

18:   N = N - 1

19: end while

20: if N > 0 then

21:   return list of subnetworks that are among the N + 1 most-regulated ones across all replicates in origSN

22: else

23:   return empty list

24: end if

The algorithm for significance evaluation in pseudocode.

Klammer et al. BMC Bioinformatics 2010 11:351   doi:10.1186/1471-2105-11-351