Evidence map›Paper›PMID 32398145›Full record

ArticleGenome biology2020

Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank.

Martin Steinegger, Steven L Salzberg

Abstract read
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 150 papers.

0numbers the graph read from it
0cells of the map it votes in
150citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

150 citing papers in PubMed.

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  15. Ecology and evolution · 2026
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  18. Review
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90 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Martin SteineggerSchool of Biological Sciences, Seoul National University, Seoul, 08826, South Korea. martin.steinegger@snu.ac.kr.
Steven L SalzbergCenter for Computational Biology, Whiting School of Engineering, Johns Hopkins University, Baltimore, 21218, Maryland, USA.

Funding

Computational Methods for Genome Assembly, Transcript Assembly, and Variant DiscoveryR01HG006677 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI SALZBERG, STEVEN L. · 2011 to 2025
$10.7M
Computational Methods for Microbial and Microbiome Sequence AnalysisR35GM130151 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Steven L. Salzberg · 2019 to 2026
$2.9M
NHGRI NIH HHS R01 HG006677NIGMS NIH HHS R35 GM130151
6 · The paper itself

Abstract

Genomic analyses are sensitive to contamination in public databases caused by incorrectly labeled reference sequences. Here, we describe Conterminator, an efficient method to detect and remove incorrectly labeled sequences by an exhaustive all-against-all sequence comparison. Our analysis reports contamination of 2,161,746, 114,035, and 14,148 sequences in the RefSeq, GenBank, and NR databases, respectively, spanning the whole range from draft to "complete" model organism genomes. Our method scales linearly with input size and can process 3.3 TB in 12 days on a 32-core computer. Conterminator can help ensure the quality of reference databases. Source code (GPLv3): https://github.com/martin-steinegger/conterminator.

Indexed as

DNA ContaminationAnimalsDatabases, Nucleic AcidGenomeHumansMiceContaminationGenBankGenomesRefSeqSoftware

Identifiers

PMID32398145
PMCPMC7218494

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.