![]() Users with long read assemblies from HGAP, Canu or Unicycler may find the options in the NGS polishing of a draft genome workflow to be more familiar. While functionally the same, we present these workflows as separate options for those who may be more familiar with either the term “polishing” or “genome finishing” to refer to the correction of internal assembly errors in the contig consensus sequences. Perform an initial polishing of the consensus sequences using either the PacBio/Nanopore workflow NGS polishing of a draft genome or the NGS-Based workflow Genome finishing – initial error correction. Therefore, among the many adantages to having a highly accurate sequence, if an accurately annotated genome is required, it is imperative that the errors be removed. As most errors are small insertions or deletions, many genes will appear to contain frameshifts. A typical 5Mb bacterial draft sequence is expected to have 25,000-50,000 errors, which translates into each gene having an average of 2-10 errors. This is equal to an error every 100-500 bases. The starting sequences generally have a base level accuracy of 99%-99.5%. ![]() However, due to the error-prone nature of long read data, the assembled sequences typically contain numerous large and small errors. The lengths of these sequences make it possible to construct topologically correct consensus sequences for each chromosome and plasmid/organelle using de novo assembly. Newer long read sequencing technologies like those from Oxford Nanopore Technologies (ONT) and PacBio produce reads that can span all but the longest repeat elements in a genome. Illumina and other NGS technologies produce highly accurate results, but the short reads can pose challenges in closing genomes. Whether you are working with Illumina, Oxford Nanopore, PacBio data, or a combination of these, assembling a complete genome can be a challenge. Choosing the right assembly strategy for NGS and long read sequencing data in SeqMan NGen
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