TY  - JOUR
A1  - King, Daniel A.
A1  - Sifrim, Alejandro
A1  - Fitzgerald, Tomas W.
A1  - Rahbari, Raheleh
A1  - Hobson, Emma
A1  - Homfray, Tessa
A1  - Mansour, Sahar
A1  - Mehta, Sarju G.
A1  - Shehla, Mohammed
A1  - Tomkins, Susan E.
A1  - Vasudevan, Pradeep C.
A1  - Hurles, Matthew E.
A1  - The Deciphering Developmental Disorders Study
T1  - Detection of structural mosaicism from targeted and whole-genome sequencing data
Y1  - 2017/10/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 1704 
EP  - 1714 
DO  - 10.1101/gr.212373.116 
VL  - 27 
IS  - 10 
UR  - http://genome.cshlp.org/content/27/10/1704.abstract 
N2  - 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. 
ER  -