Evidence map›Paper›PMID 29726617›Full record

ArticleGenes, chromosomes & cancer2018

Copy number variant analysis using genome-wide mate-pair sequencing.

James B Smadbeck, Sarah H Johnson, Stephanie A Smoley, Athanasios Gaitatzes, Travis M Drucker, Roman M Zenka, Farhad Kosari, Stephen J Murphy, Nicole Hoppman, Umut Aypar and 5 more

Abstract read
In one paragraph

Article in Genes, chromosomes & cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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  6. Optimization of the "Ecology and evolution · 2023
    Article
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  10. The Prognostic Role of MYC Structural Variants Identified by NGS and FISH in Multiple Myeloma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021
    Article
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  20. An intragenic duplication ofCold Spring Harbor molecular case studies · 2019
    Article
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

15 authors.

James B SmadbeckCenter for Individualized Medicine - Biomarker Discovery, Mayo Clinic, Rochester, Minnesota.ORCID 0000-0002-8902-0950
Sarah H JohnsonCenter for Individualized Medicine - Biomarker Discovery, Mayo Clinic, Rochester, Minnesota.
Stephanie A SmoleyDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Athanasios GaitatzesBioinformatics Systems, Mayo Clinic, Rochester, Minnesota.
Travis M DruckerBioinformatics Systems, Mayo Clinic, Rochester, Minnesota.
Roman M ZenkaBioinformatics Systems, Mayo Clinic, Rochester, Minnesota.
Farhad KosariCenter for Individualized Medicine - Biomarker Discovery, Mayo Clinic, Rochester, Minnesota.
Stephen J MurphyCenter for Individualized Medicine - Biomarker Discovery, Mayo Clinic, Rochester, Minnesota.
Nicole HoppmanDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Umut AyparDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
William R SukovDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Robert B JenkinsDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Hutton M KearneyDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
Andrew L FeldmanDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.
George VasmatzisCenter for Individualized Medicine - Biomarker Discovery, Mayo Clinic, Rochester, Minnesota.

Funding

Genetic Biomarkers for Risk Assessment of Peripheral T-Cell LymphomasR01CA177734 · NCI · MAYO CLINIC ROCHESTER · PI FELDMAN, ANDREW LEWIS · 2013 to 2017
$1.6M
NCI NIH HHS R01 CA177734
6 · The paper itself

Abstract

Copy number variation (CNV) is a common form of structural variation detected in human genomes, occurring as both constitutional and somatic events. Cytogenetic techniques like chromosomal microarray (CMA) are widely used in analyzing CNVs. However, CMA techniques cannot resolve the full nature of these structural variations (i.e. the orientation and location of associated breakpoint junctions) and must be combined with other cytogenetic techniques, such as karyotyping or FISH, to do so. This makes the development of a next-generation sequencing (NGS) approach capable of resolving both CNVs and breakpoint junctions desirable. Mate-pair sequencing (MPseq) is a NGS technology designed to find large structural rearrangements across the entire genome. Here we present an algorithm capable of performing copy number analysis from mate-pair sequencing data. The algorithm uses a step-wise procedure involving normalization, segmentation, and classification of the sequencing data. The segmentation technique combines both read depth and discordant mate-pair reads to increase the sensitivity and resolution of CNV calls. The method is particularly suited to MPseq, which is designed to detect breakpoint junctions at high resolution. This allows for the classification step to accurately calculate copy number levels at the relatively low read depth of MPseq. Here we compare results for a series of hematological cancer samples that were tested with CMA and MPseq. We demonstrate comparable sensitivity to the state-of-the-art CMA technology, with the benefit of improved breakpoint resolution. The algorithm provides a powerful analytical tool for the analysis of MPseq results in cancer.

Indexed as

Chromosome AberrationsHigh-Throughput Nucleotide SequencingAlgorithmsChromosome BreakpointsDNA Copy Number VariationsGene RearrangementGenome, HumanHumansTissue Array Analysisbioinformaticscancer geneticschromosomal rearrangementscopy number variant analysisnext-generation sequencing

Identifiers

PMID29726617
PMCPMC6117203

What OpenQuestion holds

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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.