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); |