ArticleGenome biology and evolution2018
IMPUTOR: Phylogenetically Aware Software for Imputation of Errors in Next-Generation Sequencing.
Article in Genome biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
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- Population Analysis and Evolution ofMicroorganisms · 2020Article
- Computational pan-genome mapping and pairwise SNP-distance improve detection of Mycobacterium tuberculosis transmission clusters.PLoS computational biology · 2019Article
- Highlight: New Solutions and Open Questions in Computational Evolutionary Biology.Genome biology and evolution · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce IMPUTOR, software for phylogenetically aware imputation of missing haploid nonrecombining genomic data. Targeted for next-generation sequencing data, IMPUTOR uses the principle of parsimony to impute data marked as missing due to low coverage. Along with efficiently imputing missing variant genotypes, IMPUTOR is capable of reliably and accurately correcting many nonmissing sites that represent spurious sequencing errors. Tests on simulated data show that IMPUTOR is capable of detecting many induced mutations without making erroneous imputations/corrections, with as many as 95% of missing sites imputed and 81% of errors corrected under optimal conditions. We tested IMPUTOR with human Y-chromosomes from pairs of close relatives and demonstrate IMPUTOR's efficacy in imputing missing and correcting erroneous calls.
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Registered trials
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