Perform agony computation. The software for agony computation (exact algorithm) adopted here was developed by Professor Nikolaj Tatti and colleagues. Agony is a measure of hierarchy within a directed graph. Given a directed graph and a ranking metric (e.g., in our case the time ordering of accumulation of driver alterations during tumor evolution), any arc from nodes that are higher in the hierarchy (e.g., alterations that occur in later stages of the tumor) to nodes that are lower in the hierarchy (e.g., alterations that occur at the initiation of the tumor) are not expected and they are said to be causing agony.
agony(inmatrix, seed)Output agony matrix.
The software for agony computation (exact algorithm) adopted here was developed by Professor Nikolaj Tatti and colleagues. For a detailed description, please refer to: Tatti, Nikolaj. "Tiers for peers: a practical algorithm for discovering hierarchy in weighted networks." Data mining and knowledge discovery 31.3 (2017): 702-738.
For a detailed description, please refer to: Tatti, Nikolaj. "Tiers for peers: a practical algorithm for discovering hierarchy in weighted networks." Data mining and knowledge discovery 31.3 (2017): 702-738.
data(agonyArcs)
agony(agonyArcs, 12345)
#> [,1] [,2]
#> [1,] 2 1
#> [2,] 1 2
#> [3,] 3 0