Divide-and-conquer global alignment algorithm for finding highly similar candidates of a sequence in database

Abstract

A divide-and-conquer global alignment algorithm for finding highly similar candidates of a sequence in database is disclosed. The invention gives a divide-and-conquer algorithm called Kart, that separates the given sequence into smaller pieces whose alignment can be carried out independently, and their concatenated alignment constitutes the global alignment of the entire sequence. Kart could be viewed as aligning multiple seeds simultaneously in parallel. We illustrate the idea using the read mapping of Next-generation sequencing (NGS) as an example. NGS provides a great opportunity to investigate genome-wide variation at nucleotide resolution. Due to the huge amount of data, NGS applications require very fast alignment algorithms. The invention can process long reads as fast as short reads. Furthermore, it can tolerate much higher error rates. The experiments show that Kart spends much less time on longer reads than most aligners and still produce reliable alignments.

Description

technical field [0001] The invention relates to an alignment method, in particular to an alignment method using a divide and conquer method for high similarity sequences. Background technique [0002] High-throughput sequencing (Next-generation sequencing, NGS) technology allows biologists to explore the differences between gene bodies with a precision down to nucleotide resolution, resulting in many important research discoveries. NGS has now become one of the main methods for DNA sequencing and the exploration of genome differences in ethnic groups. Because new sequencing technologies can generate millions or even billions of nucleotide sequencing data in a day, many NGS applications require fast alignment methods for the analysis of large numbers of sequences. Traditional sequence alignment methods such as BLAST[1] or BLAT[2] cannot efficiently handle such a large amount of short sequence data, so many alignment methods for NGS short sequences have been developed in rece...

AI Technical Summary

Problems solved by technology

[0005] Although there are many alignment methods that can handle the huge amount of short sequence data generated by NGS technology, some methods are not fast enough, and some methods are not accurate enough

In addition, the third-generation sequencing technology makes the comparison more challenging, and its sequencing brings longer sequences and higher error rates

For example, the PacBio RS II system can generate sequencing sequences with an average length of 5,500bp to 8,500bp, but the accuracy rate of a single sequencing sequence is only 87% on average, and most short sequence alignment methods cannot handle such sequencing data

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