A New Method to Reconstruct Recombination Events at a Genomic Scale
Figure 2
Scheme of the recombination detection process integrating 10 runs of the algorithm.
The analyzed dataset is the one shown in Figure 1. (A) Integration of the information of 10 runs regarding the recombination event of sequence 5. For each run of the algorithm, the starting and ending position of the network in which the recombination is detected, is saved. For each run, the size of the first column varies, being 10, 1, 2, 3… up to 9 and therefore the number of runs corresponds to the grain size. At the end, for each recombination event, we have a set of intervals in which it was detected which can be represented graphically as a distribution. The maximum interval represents the region in which the recombination has been seen the maximum number of times. The mean point of the maximum interval is defined as the estimated breakpoint position. The threshold indicates the number of times a recombination has to be detected to be considered as true. The intersection between the threshold and the detection distribution defines the threshold interval in which the algorithm guarantees that the recombination event is located. (B) Integration of the information of all detections for the 10 runs of the algorithm. Each line represents a set of sequences in which the same recombination event has been detected; the distribution of the line shows the number of times the event has been detected along the sequence. (C) Final output of the algorithm: breakpoint positon in the first row, the recotypes in rows and the recombination events detected in columns. The presence of a particular recombination event in a particular sequence is represented as a 1, and absence as a 0. Note that the recotypes represent exactly the coloring of the sequences in Figure 1 and that only recombinations that had a distribution above the threshold are represented in the recotypes.