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. 2021 Jun 1;7:e562. doi: 10.7717/peerj-cs.562

Algorithm 1. Algorithm of RPOS Method For Gene Selection.

1: Inputs: X,Y and number genes (r) to be selected.
2: Output: Sequence of selected genes T.
3: for all j ∈ H do
4: for c = 0,1 do
5: Compute the relative dominant class for each gene, i.e., R(j,c) in Eq. (1).
6: end for
7: for iN do
8: Compute the gene mask for each gene, i.e., mji as defined in Eq. (7).
9: Compute the RPOSjscores for each gene as defined in Eq. (9).
10: Assign RDCJ to each gene as defined in Eq. (8).
11: end for
12: let MRP×N be the gene mask matrix M = [mji], where its ithvalue for jthgene is either 0 or 1.
13: Compute the total or aggregate mask of genes and denote it by M..(H).
14: Use the Greedy search approach to select the minimum subset of genes from M, M..(H) and RPOSj and denote it by H*.
15: Perform H = HH*, this will exclude the genes selected in minimum subset from the whole set of genes.
16: Arrange the genes in RDCjin the increasing order of RPOSJ for each class.
17: end for
18: Obtaining final listed or ranked genes.
19: if r ≤ |H*| then
20: Then T includes the genes which are first r genes in H*.
21: while |T| < r do
22: Increase T by one gene in a round-robin fashion method.
23: end while
24: end if
25: return T