Qudaich: A smart sequence aligner

Abstract

Next generation sequencing (NGS) technology produces massive amounts of data in a reasonable time and low cost. Analyzing and annotating these data requires sequence alignments to compare them with genes, proteins and genomes in different databases. Sequence alignment is the first step in metagenomics analysis, and pairwise comparisons of sequence reads provide a measure of similarity between environments. Most of the current aligners focus on aligning NGS datasets against long reference sequences rather than comparing between datasets. As the number of metagenomes and other genomic data increases each year, there is a demand for more sophisticated, faster sequence alignment algorithms. Here, we introduce a novel sequence aligner, Qudaich, which can efficiently process large volumes of data and is suited to de novo comparisons of next generation reads datasets. Qudaich can handle both DNA and protein sequences and attempts to provide the best possible alignment for each query sequence. Qudaich can produce more useful alignments quicker than other contemporary alignment algorithms.\n\nAuthor SummaryThe recent developments in sequencing technology provides high throughput sequencing data and have resulted in large volumes of genomic and metagenomic data available in public databases. Sequence alignment is an important step for annotating these data. Many sequence aligners have been developed in last few years for efficient analysis of these data, however most of them are only able to align DNA sequences and mainly focus on aligning NGS data against long reference genomes. Therefore, in this study we have designed a new sequence aligner, qudaich, which can generate pairwise local sequence alignment (at both the DNA and protein level) between two NGS datasets and can efficiently handle the large volume of NGS datasets. In qudaich, we introduce a unique sequence alignment algorithm, which outperforms the traditional approaches. Qudaich not only takes less time to execute, but also finds more useful alignments than contemporary aligners.