Volume 61, Issue 2
RESEARCH PAPER

Goodness‐of‐fit tests for disorder detection in NGS experiments

Norman Jiménez‐Otero

Corresponding Author

E-mail address: njimenez@uvigo.es

SiDOR Research Group & CINBIO, University of Vigo, Vigo, Pontevedra, Spain

Correspondence

Norman Jiménez‐Otero, SiDOR Research Group, and CINBIO, University of Vigo, Campus Universitario s/n, 36310 Vigo, Pontevedra, Spain.

Email: njimenez@uvigo.es

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Jacobo de Uña‐Álvarez

Department of Statistics and Operations Research, SiDOR Research Group & CINBIO, University of Vigo, Vigo, Pontevedra, Spain

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Juan Carlos Pardo‐Fernández

Department of Statistics and Operations Research, SiDOR Research Group & CINBIO, University of Vigo, Vigo, Pontevedra, Spain

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First published: 27 December 2018

Abstract

Next‐generation sequencing (NGS) experiments are often performed in biomedical research nowadays, leading to methodological challenges related to the high‐dimensional and complex nature of the recorded data. In this work we review some of the issues that arise in disorder detection from NGS experiments, that is, when the focus is the detection of deletion and duplication disorders for homozygosity and heterozygosity in DNA sequencing. A statistical model to cope with guanine/cytosine bias and phasing and prephasing phenomena at base level is proposed, and a goodness‐of‐fit procedure for disorder detection is derived. The method combines the proper evaluation of local p‐values (one for each DNA base) with suitable corrections for multiple comparisons and the discrete nature of the p‐values. A global test for the detection of disorders in the whole DNA region is proposed too. The performance of the introduced procedures is investigated through simulations. A real data illustration is provided.

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