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. 2021 Nov 14;22(1):312.
doi: 10.1186/s13059-021-02527-4.

Accurate long-read de novo assembly evaluation with Inspector

Yu Chen  1   2 , Yixin Zhang  3 , Amy Y Wang  2   4 , Min Gao  2   5 , Zechen Chong  6   7
Affiliations

Accurate long-read de novo assembly evaluation with Inspector

Yu Chen et al. Genome Biol. .

Abstract

Long-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

Keywords: Assembly error; Assembly evaluation; De novo assembly; Genome assembly; Long reads.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Inspector workflow for evaluating of de novo assembly results. By mapping the long reads to the contigs, besides basic statistic assembly evaluation metrics, Inspector calculates and reports precise structural errors and small-scale errors. The identified errors can also be corrected by Inspector to generate more accurate contigs
Fig. 2
Fig. 2
Characterization of structural assembly errors in HG002 assemblies. a Pie charts showing the proportion of four types of structural errors identified in Canu, Flye, wtdbg2, hifiasm, and Shasta assemblies with CLR, HiFi, and Nanopore datasets, respectively. The number of assembly error is also marked on each sector. b Size distribution of identified structural assembly errors in all HG002 assemblies
Fig. 3
Fig. 3
Enrichment of assembly errors in repetitive regions. a Proportion of assembly errors located in repetitive regions in each assembly. Dashed line indicates fraction of human reference genome annotated as repeats. P values were calculated by one-sample t-test to compare the proportion of assembly errors with the baseline. b Repeat annotation of structural and small-scale errors for five assemblers
Fig. 4
Fig. 4
Improved assembly accuracy after error correction. a Methods of assembly error correction for small-scale and structural errors. b, c Number of corrected structural (b) and small-scale errors (c) in HG002 assembly. Negative values indicate more assembly errors after the polishing process
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