Detecting a Portion of Structural Variation of Hedou12 by Using Some Characteristics of the Next Sequencing Technology

Abstract

At present, the computable methods which detect structural variations (SVs) of genome have numerous been used in human genome, but are few in plant genome. If we use these methods for plant, many structural variations might not be found. Although we can find some structural variations, the valid SVs in them are very few. To enhance precision of detecting structural variations and reduce the false discovery rate in plant, we design an algorithm based on characteristics of the Hedou12 which is one of the important economic corps. The core of the algorithm composes discordant paired-end read analysis model and split-read analysis model, and set cover based on greedy heuristic method. To increase precision of detecting SVs, we separately apply the probability model of discordant paired-end reads and the probability model of split-reads as optimization selection for SVs. And by validity verification, our algorithm can increase precision of detecting SVs.