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Table 1 Overview of significance evaluation

From: Identifying differentially regulated subnetworks from phosphoproteomic data

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}mwithout {(-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
  1. The algorithm for significance evaluation in pseudocode.