PT  - JOURNAL ARTICLE
AU  - Daniel A. King
AU  - Alejandro Sifrim
AU  - Tomas W. Fitzgerald
AU  - Raheleh Rahbari
AU  - Emma Hobson
AU  - Tessa Homfray
AU  - Sahar Mansour
AU  - Sarju G. Mehta
AU  - Mohammed Shehla
AU  - Susan E. Tomkins
AU  - Pradeep C. Vasudevan
AU  - Matthew E. Hurles
AU  - The Deciphering Developmental Disorders Study
TI  - Detection of structural mosaicism from targeted and whole-genome sequencing data
AID  - 10.1101/062620
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 062620
4099  - http://biorxiv.org/content/early/2016/07/07/062620.short
4100  - http://biorxiv.org/content/early/2016/07/07/062620.full
AB  - 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 4,911 patients with undiagnosed developmental disorders, and 11 events in 9 patients were detected. In 8 of 11 cases, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly more than 50%, of mosaic diagnostic chromosomal rearrangements.