Ultra-Fast, Accurate and Cost-Effective NGS Read Alignment Validated for Complex Whole Plant Genomes

The ever-increasing output of Next Generation Sequencing (NGS) puts equally increasing demands on compute resources including computing power, processing time and data storage capacity. We aimed at designing a software solution that reduces these compute resources, while retaining or improving the accuracy.

We developed a NGS short read alignment tool based on a novel alignment algorithm and state-of-the-art high performance computing software. It reports its alignment result in the GENALICE Aligned Reads (GAR) format, which has a significantly reduced data storage footprint, is fully realignable and compatible with existing open source bioinformatics tools through a tool kit conversion. We tested the tool, GENALICE MAP, to address its performance and accuracy.

Our software aligns short reads at a speed of 40 to 130 Megabases per second depending on the percentage of variants within a dataset. The accuracy is for standard jobs at least on par with existing popular read alignment tools such as BWA and shows superiority on mapping long INDELs. The output GAR format has an up to 100-fold reduced data storage footprint compared to the widely used BAM/FASTQ formats combination.

We conclude that GENALICE MAP greatly reduces the computing power and processing time needed to align NGS short reads, while being highly accurate. Moreover, the GAR format minifies data storage capacity and facilitates data sharing. GENALICE MAP is a cost effective alternative, even when compared to open source read alignment tools, due to its high speed, limited computing power requirements and strongly reduced data storage footprint.