A fast microbial detection algorithm based on high-throughput sequencing data

Abstract

Objective Design a rapid microbial detection algorithm that analyzes the sequencing data while sequencing, which can improve the speed of pathogenic microbial detection. Method A 'analysis while sequencing' method is used to analyze the sequencing data, the method uses the detection algorithm to analyze the sequencing data generated by the sequencer periodically. The reference microbial genomes are grouped. For each group the algorithm extracts sequencing reads mapped to the microbial genomes and then filters the human genome data, then the algorithm assembles the reads left and aligns the assembled contigs to the microbial genomes. Result For the simulated data, the new algorithm achieves speedup of 10 compared with RINS when the microorganisms in the sample have ref-genomes, both results are consistent and the new algorithm gets longer contigs. The new algorithm achieves an average speedup of 9 with no ref-genomes, and it obtains more complete sequence. For the real data, the new algorithm achieves an average speedup of 3 compared with RINS, and both detection results are the same. When verifying the Sequencing-by-side method, a reliable result can be obtained with a certain scale of sequencing data. Conclusion The 'analysis while sequencing' methods can improve pathogen detection speed, and have good application prospects.