Research On Recognition Algorithm Of Genome Rearrangements

Genome rearrangement is a common form of variation in the human genome.The changes are actually the process of a series of genome rearrangement events in the genome during the evolution of the species.Through the study of genome rearrangement,it not only helps humans to understand the evolutionary history and evolutionary mechanism of species,but also has important application value in biopharmaceutical,tumor research and other application fields,so the recognition of genome rearrangement events has become an important area of bioinformatics research.At present,researchers have proposed a number of algorithms for the recognition of genome rearrangement events.The EMRAE algorithm is an algorithm for identifying ancestor rearrangement events by identifying conserved adjacencies on a fixed phylogenetic tree and using inference rules.The criterion for evaluating the algorithm is the accuracy of rearrangement recovery.The EMRAE algorithm can predict more types of rearrangement events,including inversion,transposition,translocation,fussion and fission,but the accuracy of recovering ancestral rearrangement events needs to be improved.This paper mainly studies the EMRAE algorithm,and improves the algorithm,then obtains a new algorithm,IEMRAE algorithm,which uses the Java language to add conserved adjacencies with overlapping genes and adjacencies on each edge of the phylogenetic tree.Identifying more conserved adjacencies associated with rearrangement events,using inference rules to recover more accurate ancestor rearrangement events.The simulation data is generated,and then the simulated data is used to compare the EMRAE algorithm and the IEMRAE algorithm respectively.The experimental results show that the IEMRAE algorithm can achieve higher sensitivity and specificity than the EMRAE algorithm.Applying the EMRAE algorithm and the IEMRAE algorithm to the actual data,the IEMRAE algorithm recovers more and more accurate ancestor rearrangement events than the EMRAE algorithm.Among them,48 genome rearrangement events were identified at 10 kb resolution,and 21 genome rearrangements were identified at 50 kb resolution.