Table 4

Algorithm 4 (LinearWeightedMOI)


Input: sorted list of intervals interval[1..n]; number of collections k; weight of the collections weight[1..k]; length l of the target genome; minimum weight a weighted MOI must have minWeight

Variables: largest end point seen so far in each collection endPoint[1..k]; c[0..l]

1: endPoint[1..k] 0

2: prevEnd ← 0

3: min ← 0

4: openWeight ← 0

5: c[0..l] 0

6: for all <a onClick="popup('http://www.biomedcentral.com/1471-2105/13/S19/S7/mathml/M4','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/13/S19/S7/mathml/M4">View MathML</a>interval[1..n] do

7:     if end >endPoint[j] then

8:         c[endPoint[j]] ← c[endPoint[j]] - weight[j]

9:         c[end] ← c[end] + weight[j]

10:       if endPoint[j] < min and end min then

11:         openWeight ← openWeight + weight[j]

12:       end if

13:       endPoint[j] = end

14:   end if

15:   if all intervals with recent start position processed then

16:       while openWeight - c[min] ≥ minWeight do

17:         openWeight ← openWeight - c[min]

18:         min ← min + 1

19:       end while

20:       if prevEnd < min and min ≥ start then

21:         output MOI(start, min)

22:         prevEnd ← min

23:       end if

24:   end if

25: end for


Jahn et al. BMC Bioinformatics 2012 13(Suppl 19):S7   doi:10.1186/1471-2105-13-S19-S7

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