From: gammaMAXT: a fast multiple-testing correction algorithm
(1) Each cluster node \(c=1\dots C\) performs an equitable fraction of the computations of the T 0,1,…,T 0,m |
values from Fig. 1. The n highest values (and corresponding SNP pair indexes) from each node are saved |
into file top_c.txt. |
(2) Upon termination of all computations at the previous step, a cluster node aggregates all top_c.txt files and |
retrieves the overall n highest values (and corresponding SNP pair indexes). Results are saved into topfile.txt. |
(3) Each cluster node reads topfile.txt, initialize a vector V of size n with 0’s and performs an equitable fraction |
of the B permutations of Fig. 1. For each permutation i attributed to node c: |
(a) Generate a random permutation of the trait column. |
(b) Compute T i,1,…,T i,n and store them in a Permutation i vector. |
(c) Execute step (3)(c) of the gammaMAXT algorithm to estimate M i . |
(d) Replace T i,n by M i if T i,n <M i . |
(e) Force the monotonicity of the Permutation i vector: for j=n−1,…,1 replace T i,j by T i,j+1 if T i,j <T i,j+1. |
(f) For each j=1,…,n, if T i,j ≥T 0,j increment V j by one. |
Upon completion of all computations on node c, save V into file permut_c.txt. |
(4) A cluster node sums all vectors from the permut_c.txt files to obtain a vector p. All elements of p are |
incremented by 1 and divided by B+1. The monotonicity is forced: for j=1,…,n−1, replace p j+1 by p j |
if p j+1<p j . |