Evidence map›Paper›PMID 28742110›Full record

ArticlePloS one2017

Evaluation of exome variants using the Ion Proton Platform to sequence error-prone regions.

Heewon Seo, Yoomi Park, Byung Joo Min, Myung Eui Seo, Ju Han Kim

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Heewon SeoSeoul National University Biomedical Informatics (SNUBI), Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.
Yoomi ParkSeoul National University Biomedical Informatics (SNUBI), Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.
Byung Joo MinSeoul National University Biomedical Informatics (SNUBI), Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.
Myung Eui SeoSeoul National University Biomedical Informatics (SNUBI), Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.
Ju Han KimSeoul National University Biomedical Informatics (SNUBI), Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Ion Proton sequencer from Thermo Fisher accurately determines sequence variants from target regions with a rapid turnaround time at a low cost. However, misleading variant-calling errors can occur. We performed a systematic evaluation and manual curation of read-level alignments for the 675 ultrarare variants reported by the Ion Proton sequencer from 27 whole-exome sequencing data but that are not present in either the 1000 Genomes Project and the Exome Aggregation Consortium. We classified positive variant calls into 393 highly likely false positives, 126 likely false positives, and 156 likely true positives, which comprised 58.2%, 18.7%, and 23.1% of the variants, respectively. We identified four distinct error patterns of variant calling that may be bioinformatically corrected when using different strategies: simplicity region, SNV cluster, peripheral sequence read, and base inversion. Local de novo assembly successfully corrected 201 (38.7%) of the 519 highly likely or likely false positives. We also demonstrate that the two sequencing kits from Thermo Fisher (the Ion PI Sequencing 200 kit V3 and the Ion PI Hi-Q kit) exhibit different error profiles across different error types. A refined calling algorithm with better polymerase may improve the performance of the Ion Proton sequencing platform.

Indexed as

ExomeAlgorithmsBase SequenceFalse Positive ReactionsGenetic LociGenome, HumanHigh-Throughput Nucleotide SequencingHumansINDEL MutationPolymorphism, Single NucleotideSequence AlignmentSequence Analysis, DNA

Identifiers

PMID28742110
PMCPMC5524428

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Registered trials

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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.