Abstract Motivation In the modern genomics era, genome sequence assemblies are routine practice. However, depending on the methodology, resulting drafts may contain considerable base errors. Although utilities exist for genome… Click to show full abstract
Abstract Motivation In the modern genomics era, genome sequence assemblies are routine practice. However, depending on the methodology, resulting drafts may contain considerable base errors. Although utilities exist for genome base polishing, they work best with high read coverage and do not scale well. We developed ntEdit, a Bloom filter-based genome sequence editing utility that scales to large mammalian and conifer genomes. Results We first tested ntEdit and the state-of-the-art assembly improvement tools GATK, Pilon and Racon on controlled Escherichia coli and Caenorhabditis elegans sequence data. Generally, ntEdit performs well at low sequence depths (<20×), fixing the majority (>97%) of base substitutions and indels, and its performance is largely constant with increased coverage. In all experiments conducted using a single CPU, the ntEdit pipeline executed in <14 s and <3 m, on average, on E.coli and C.elegans, respectively. We performed similar benchmarks on a sub-20× coverage human genome sequence dataset, inspecting accuracy and resource usage in editing chromosomes 1 and 21, and whole genome. ntEdit scaled linearly, executing in 30–40 m on those sequences. We show how ntEdit ran in <2 h 20 m to improve upon long and linked read human genome assemblies of NA12878, using high-coverage (54×) Illumina sequence data from the same individual, fixing frame shifts in coding sequences. We also generated 17-fold coverage spruce sequence data from haploid sequence sources (seed megagametophyte), and used it to edit our pseudo haploid assemblies of the 20 Gb interior and white spruce genomes in <4 and <5 h, respectively, making roughly 50M edits at a (substitution+indel) rate of 0.0024. Availability and implementation https://github.com/bcgsc/ntedit Supplementary information Supplementary data are available at Bioinformatics online.
               
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