U ₅₀ : A New Metric for Measuring Assembly Output Based on Non-Overlapping, Target-Specific Contigs

Abstract

Advances in next-generation sequencing technologies enable routine genome sequencing, generating millions of short reads. A crucial step for full genome analysis is the de novo assembly, and currently, performance of different assembly methods is measured by a metric called N₅₀. However, the N₅₀ value can produce skewed, inaccurate results when complex data are analyzed, especially for viral and microbial datasets. To provide a better assessment of assembly output, we developed a new metric called U₅₀. The U₅₀ identifies unique, target-specific contigs by using a reference genome as baseline, aiming at circumventing some limitations that are inherent to the N₅₀ metric. Specifically, the U₅₀ program removes overlapping sequence of multiple contigs by utilizing a mask array, so the performance of the assembly is only measured by unique contigs. We compared simulated and real datasets by using U₅₀ and N₅₀, and our results demonstrated that U₅₀ has the following advantages over N₅₀: (1) reducing erroneously large N₅₀ values due to a poor assembly, (2) eliminating overinflated N₅₀ values caused by large measurements from overlapping contigs, (3) eliminating diminished N₅₀ values caused by an abundance of small contigs, and (4) allowing comparisons across different platforms or samples based on the new percentage-based metric UG₅₀%. The use of the U₅₀ metric allows for a more accurate measure of assembly performance by analyzing only the unique, non-overlapping contigs. In addition, most viral and microbial sequencing have high background noise (i.e., host and other non-targets), which contributes to having a skewed, misrepresented N₅₀ value-this is corrected by U₅₀. Also, the UG₅₀% can be used to compare assembly results from different samples or studies, the cross-comparisons of which cannot be performed with N₅₀.