U50: A New Metric for Measuring Assembly Output Based on Non-Overlapping, Target-Specific Contigs

Details

• Alternative Title:
  J Comput Biol
• Personal Author:
  Castro, Christina J. ; Ng, Terry Fei Fan
• Description:
  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 N|. However, the N| 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 U|. The U| identifies unique, target-specific contigs by using a reference genome as baseline, aiming at circumventing some limitations that are inherent to the N| metric. Specifically, the U| 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 U| and N|, and our results demonstrated that U| has the following advantages over N|: (1) reducing erroneously large N| values due to a poor assembly, (2) eliminating overinflated N| values caused by large measurements from overlapping contigs, (3) eliminating diminished N| values caused by an abundance of small contigs, and (4) allowing comparisons across different platforms or samples based on the new percentage-based metric UG|%. The use of the U| 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 N| value-this is corrected by U|. Also, the UG|% can be used to compare assembly results from different samples or studies, the cross-comparisons of which cannot be performed with N|.
• Subjects:
  Algorithms Article Contig Mapping Genome, Bacterial Genome, Viral Genome Assembly Genomics High-Throughput Nucleotide Sequencing Humans N50 Next-generation Sequencing Sequence Analysis, DNA Software U50

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• Source:
  J Comput Biol. 24(11):1071-1080
• Pubmed ID:
  28418726
• Pubmed Central ID:
  PMC5783553
• Document Type:
  Journal Article
• Funding:
  CC999999/Intramural CDC HHS/United States
• Volume:
  24
• Issue:
  11
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:0a51bb7a3430bf85108086a6793f91fac1de6dcc30959469297d82b0d4ca5ff0
• Download URL:
  https://stacks.cdc.gov/view/cdc/51161/cdc_51161_DS1.pdf
• File Type:
  [PDF - 652.84 KB ]