基于长种子的二代测序序列找全比对算法

Sequence All-mapper for Next-generation Sequencing Based on Long Seed

主流的二代测序序列找全比对算法采用种子扩展的方法,由于长种子索引存在空间开销大或检索时间长的问题,这类算法大多使用短种子而导致候选位置过多,增加了比对的时间成本.为此,提出一种基于长种子的找全比对算法,设计了一种空间开销低和检索时间适度的长种子哈希索引,其通过模运算限制哈希空间并使用布隆过滤器识别同一存储位置上的不同种子.长种子显著减少候选位置数量,从而降低验证阶段的时间开销.实验结果表明,在人类基因序列测序数据集上,该算法维持同等精度的同时比现有主流算法时间效率更高.

The mainstream all-mappers of next-generation sequencing mostly use the seed-and-extend method.Due to high storage costs or long retrieval time of the long-seed index,most of these algorithms use short seeds,which results in redundant candidate positions and increases the time cost of alignment.We,therefore,propose an all-mapper based on long seeds,and a long-seed hash index with low storage costs and moderate retrieval time is designed.The long-seed hash index limits the hash space through modular operation and uses the Bloom filter to identify different seeds at the same storage location.Long seeds significantly reduce the number of candidate locations and thus lower the time cost in the verification phase.The experiments on human gene sequencing datasets reveal that the proposed all-mapper has higher time efficiency than the existing mainstream all-mappers while maintaining the same accuracy.