基于长读数和重比对的倒位变异检测方法

Inversion variation detection method based on long reads and realignment

结构变异检测是基因组大数据分析的一项重要任务,其中倒位变异是一种常见的结构变异,并往往与多种严重的疾病相关联,因此获取准确的倒位变异发生位置是一项具有重要研究意义的工作。提出了一种基于长读数和重比对的倒位变异检测方法,首先在长读数和基因组参考序列比对结果中提取每条长读数被剪切掉的序列;然后将剪切序列重新比对到基因组参考序列上,基于原始的比对信息和剪切序列的比对信息确定倒位变异信号;最后,对倒位变异信号进行聚类确定倒位变异发生的位置。该方法与较常见的其他两种倒位变异检测方法在两组数据集上进行了性能比较,实验结果表明该方法能取得更令人满意的检测结果。

Structural variation detection is an important task of genome big data analysis.Inversion is a common structural variation and is often associated with a variety of serious diseases.Therefore,obtaining the accurate position of inversion is an important task.This paper proposed a method for detecting inversions variation based on long reads and realignment.This method firstly extracted the clipped sequence of each long read,and aligned them against the genome reference sequence.Based on the original alignment information and the realignment information,this method determined the inversion signals.Finally,it clustered the inversion signals to determine the location of the inversions.The performance of this method and the other two common inversion variation detection methods were compared on two datasets.The experimental results show that this method can obtain more satisfactory detection results.