Evidence map›Paper›PMID 26384417›Full record

ArticleNucleic acids research2016

Targeted single molecule mutation detection with massively parallel sequencing.

Mark T Gregory, Jessica A Bertout, Nolan G Ericson, Sean D Taylor, Rithun Mukherjee, Harlan S Robins, Charles W Drescher, Jason H Bielas

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

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  16. Considerations and quality controls when analyzing cell-free tumor DNA.Biomolecular detection and quantification · 2019
    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

8 authors.

Mark T GregoryTranslational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Jessica A BertoutTranslational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Nolan G EricsonTranslational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Sean D TaylorTranslational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Rithun MukherjeeComputational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Harlan S RobinsComputational Biology Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Charles W DrescherTranslational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Jason H BielasTranslational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA Department of Pathology, University of Washington, Seattle, WA 98195, USA jbielas@fredhutch.org.

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
Vaccinating against IGFBP-2 to prevent ovarian cancer relapseP50CA083636 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI DRESCHER, CHARLES, URBAN, NICOLE DENISE · 1999 to 2015
$35.1M
Mechanisms of Environmental and Nuclear and Mitochondrial MutagenesisR01ES019319 · NIEHS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BIELAS, JASON H · 2010 to 2014
$2.5M
Dissecting the role of mitochondrial DNA mutations in cancerF32ES021703 · NIEHS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI TAYLOR, SEAN DAVID · 2012 to 2013
$85k
NCI NIH HHS P30 CA015704NCI NIH HHS P50 CA083636NIEHS NIH HHS F32ES021703NIEHS NIH HHS R01 ES019319NIEHS NIH HHS R01ES019319
6 · The paper itself

Abstract

Next-generation sequencing (NGS) technologies have transformed genomic research and have the potential to revolutionize clinical medicine. However, the background error rates of sequencing instruments and limitations in targeted read coverage have precluded the detection of rare DNA sequence variants by NGS. Here we describe a method, termed CypherSeq, which combines double-stranded barcoding error correction and rolling circle amplification (RCA)-based target enrichment to vastly improve NGS-based rare variant detection. The CypherSeq methodology involves the ligation of sample DNA into circular vectors, which contain double-stranded barcodes for computational error correction and adapters for library preparation and sequencing. CypherSeq is capable of detecting rare mutations genome-wide as well as those within specific target genes via RCA-based enrichment. We demonstrate that CypherSeq is capable of correcting errors incurred during library preparation and sequencing to reproducibly detect mutations down to a frequency of 2.4 × 10(-7) per base pair, and report the frequency and spectra of spontaneous and ethyl methanesulfonate-induced mutations across the Saccharomyces cerevisiae genome.

Indexed as

MutationCell LineDNAGenes, p53High-Throughput Nucleotide SequencingHumansPolymerase Chain ReactionSaccharomyces cerevisiaeDNA

Identifiers

PMID26384417
PMCPMC4756847

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.