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Fig. 2 | BMC Bioinformatics

Fig. 2

From: A nearest-neighbors network model for sequence data reveals new insight into genotype distribution of a pathogen

Fig. 2

An example illustrating the workings of the DiWANN network construction algorithm. To the left is the distance matrix produced by Algorithm 1, and to the right is the DiWANN graph constructed using this distance matrix. The example has 10 sequences drawn from the A. marginale SSRs. Because the distance matrix is symmetric, Algorithm 1 uses only its upper diagonal half, while the unused portion is in black. The first row of the matrix, which must always be computed, is shown in yellow. Every cell in which a distance is computed but is not used in building the DiWANN graph is shown in red. A cell in which a distance is pruned because it wouldn’t result in an edge in the DiWANN graph is shown with entry of infinity. All other non-infinite cell values, shown in green, correspond to edges in the graph. For each sequence, A-O, an outgoing edge is added to the sequence (sequences) that is (are) at the minimum distance from itself (corresponds to rowMin at the end of a row computation in Algorithm 1). Note that the edge from node O is not bidirectional

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