Table 1.

Algorithm for clustering indels into candidate redundant indel groups

Algorithm 1:	Clustering indels into candidate redundant indel groups Algorithm
Input:	An indel List: List (I) ordered by indel positions on the reference genome, each indel I has position P, threshold value D of distance between adjacent indels
Output:	Candidate redundant indel groups List List (G k)
1	Candidate-Group-Generation (indel list: List(I), threshold-value: D)
2	Set List (G k) empty: Ø;
3	Set k = 0;
4	Set current indel I current = I 0, the first element in the List (I);
5	for each indel i = 2 to n in indel list List (I)
6	if next adjacent indel I i’s position P i - P current < = D then
7	Add the next indel into the current candidate group G (k);
8	Set current indel I current = I i;
9	else
10	Append G(k) to candidate group list List (G k);
11	k = k + 1;
12	end
13	return candidate redundant group list List (G k);