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Detection of structural mosaicism from targeted and whole-genome sequencing data.

King, DA; Sifrim, A; Fitzgerald, TW; Rahbari, R; Hobson, E; Homfray, T; Mansour, S; Mehta, SG; Shehla, M; Tomkins, SE; et al. King, DA; Sifrim, A; Fitzgerald, TW; Rahbari, R; Hobson, E; Homfray, T; Mansour, S; Mehta, SG; Shehla, M; Tomkins, SE; Vasudevan, PC; Hurles, ME; Deciphering Developmental Disorders Study, (2017) Detection of structural mosaicism from targeted and whole-genome sequencing data. Genome Res, 27 (10). pp. 1704-1714. ISSN 1549-5469 https://doi.org/10.1101/gr.212373.116
SGUL Authors: Mansour, Sahar Mansour, Sahar

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Abstract

Structural mosaic abnormalities are large post-zygotic mutations present in a subset of cells and have been implicated in developmental disorders and cancer. Such mutations have been conventionally assessed in clinical diagnostics using cytogenetic or microarray testing. Modern disease studies rely heavily on exome sequencing, yet an adequate method for the detection of structural mosaicism using targeted sequencing data is lacking. Here, we present a method, called MrMosaic, to detect structural mosaic abnormalities using deviations in allele fraction and read coverage from next-generation sequencing data. Whole-exome sequencing (WES) and whole-genome sequencing (WGS) simulations were used to calculate detection performance across a range of mosaic event sizes, types, clonalities, and sequencing depths. The tool was applied to 4911 patients with undiagnosed developmental disorders, and 11 events among nine patients were detected. For eight of these 11 events, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly >50%, of mosaic diagnostic chromosomal rearrangements.

Item Type: Article
Additional Information: © 2017 King et al.; Published by Cold Spring Harbor Laboratory Press (http://genome.cshlp.org/site/misc/terms.xhtml) This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
Keywords: Bioinformatics, 06 Biological Sciences, 11 Medical And Health Sciences
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Genome Res
ISSN: 1549-5469
Language: eng
Dates:
DateEvent
October 2017Published
30 August 2017Published Online
18 July 2017Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
HICF-1009-003Wellcome Trusthttp://dx.doi.org/10.13039/100004440
HICF-1009-003Department of Healthhttp://dx.doi.org/10.13039/501100000276
WT098051Wellcome Trusthttp://dx.doi.org/10.13039/100004440
PubMed ID: 28855261
Web of Science ID: WOS:000412119200009
Go to PubMed abstract
URI: http://openaccess.sgul.ac.uk/id/eprint/109308
Publisher's version: https://doi.org/10.1101/gr.212373.116

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