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Using population data for assessing next-generation sequencing performance

Lookup NU author(s): Darren Houniet, Dr Thahira Rahman, Dr Yaobo Xu, Professor Judith Goodship, Professor Bernard Keavney

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2014 The Author. Published by Oxford University Press. Motivation: During the past 4 years, whole-exome sequencing has become a standard tool for finding rare variants causing Mendelian disorders. In that time, there has also been a proliferation of both sequencing platforms and approaches to analyse their output. This requires approaches to assess the performance of different methods. Traditionally, criteria such as comparison with microarray data or a number of known polymorphic sites have been used. Here we expand such approaches, developing a maximum likelihood framework and using it to estimate the sensitivity and specificity of whole-exome sequencing data. Results: Using whole-exome sequencing data for a panel of 19 individuals, we show that estimated sensitivity and specificity are similar to those calculated using microarray data as a reference. We explore the effect of frequency misspecification arising from using an inappropriately selected population and find that, although the estimates are affected, the rankings across procedures remain the same. Availability and implementation: An implementation using Perl and R can be found at busso.ncl.ac.uk (Username: igm101; Password: Z1z1nts). Contact:; mauro.santibanez-koref@newcastle.ac.uk


Publication metadata

Author(s): Houniet DT, Rahman TJ, Al Turki S, Hurles ME, Xu Y, Goodship J, Keavney B, Koref MS

Publication type: Article

Publication status: Published

Journal: Bioinformatics

Year: 2015

Volume: 31

Issue: 1

Pages: 56-61

Print publication date: 01/01/2015

Online publication date: 17/09/2014

Acceptance date: 05/09/2014

Date deposited: 18/07/2017

ISSN (print): 1367-4803

ISSN (electronic): 1460-2059

Publisher: Oxford University Press

URL: https://doi.org/10.1093/bioinformatics/btu606

DOI: 10.1093/bioinformatics/btu606

PubMed id: 25236458


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Funding

Funder referenceFunder name
S.A.T. and M.E.H. were funded by the Wellcome Trust [Grant Number: WT098051]
This work was supported by the British Heart Foundation [Grant reference: FS/10/008/28146]

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