Error and error mitigation in low-coverage genome assemblies

Hubisz, M. J., Lin, M. F., Kellis, M., Siepel, A. (2011) Error and error mitigation in low-coverage genome assemblies. PLoS One, 6 (2). e17034. ISSN 1932-6203

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DOI: 10.1371/journal.pone.0017034


The recent release of twenty-two new genome sequences has dramatically increased the data available for mammalian comparative genomics, but twenty of these new sequences are currently limited to approximately 2x coverage. Here we examine the extent of sequencing error in these 2x assemblies, and its potential impact in downstream analyses. By comparing 2x assemblies with high-quality sequences from the ENCODE regions, we estimate the rate of sequencing error to be 1-4 errors per kilobase. While this error rate is fairly modest, sequencing error can still have surprising effects. For example, an apparent lineage-specific insertion in a coding region is more likely to reflect sequencing error than a true biological event, and the length distribution of coding indels is strongly distorted by error. We find that most errors are contributed by a small fraction of bases with low quality scores, in particular, by the ends of reads in regions of single-read coverage in the assembly. We explore several approaches for automatic sequencing error mitigation (SEM), making use of the localized nature of sequencing error, the fact that it is well predicted by quality scores, and information about errors that comes from comparisons across species. Our automatic methods for error mitigation cannot replace the need for additional sequencing, but they do allow substantial fractions of errors to be masked or eliminated at the cost of modest amounts of over-correction, and they can reduce the impact of error in downstream phylogenomic analyses. Our error-mitigated alignments are available for download.

Item Type: Paper
Uncontrolled Keywords: Animals Chromosome Mapping/methods Databases, Nucleic Acid/*standards Genome/genetics Genomics/methods Humans Mammals/genetics Molecular Sequence Annotation/methods/*standards *Research Design Sequence Analysis, DNA/methods/*standards
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > genomes
CSHL Authors:
Communities: CSHL labs > Siepel lab
Depositing User: Matt Covey
Date: 2011
Date Deposited: 14 Jan 2015 20:13
Last Modified: 14 Jan 2015 20:13
PMCID: PMC3038916
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