Jump to ContentJump to Main Navigation
Show Summary Details

Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Stumpf, Michael P.H.

6 Issues per year

IMPACT FACTOR increased in 2015: 1.265
5-year IMPACT FACTOR: 1.423
Rank 42 out of 123 in category Statistics & Probability in the 2015 Thomson Reuters Journal Citation Report/Science Edition

SCImago Journal Rank (SJR) 2015: 0.954
Source Normalized Impact per Paper (SNIP) 2015: 0.554
Impact per Publication (IPP) 2015: 1.061

Mathematical Citation Quotient (MCQ) 2015: 0.06

See all formats and pricing
Volume 9, Issue 1 (Jun 2010)

Locating Multiple Interacting Quantitative Trait Loci with the Zero-Inflated Generalized Poisson Regression

Vinzenz Erhardt
  • Technische Universität München
/ Malgorzata Bogdan
  • Wroclaw University of Technology and Purdue University
/ Claudia Czado
  • Technische Universität München
Published Online: 2010-06-22 | DOI: https://doi.org/10.2202/1544-6115.1545

We consider the problem of locating multiple interacting quantitative trait loci (QTL) influencing traits measured in counts. In many applications the distribution of the count variable has a spike at zero. Zero-inflated generalized Poisson regression (ZIGPR) allows for an additional probability mass at zero and hence an improvement in the detection of significant loci. Classical model selection criteria often overestimate the QTL number. Therefore, modified versions of the Bayesian Information Criterion (mBIC and EBIC) were successfully used for QTL mapping. We apply these criteria based on ZIGPR as well as simpler models. An extensive simulation study shows their good power detecting QTL while controlling the false discovery rate. We illustrate how the inability of the Poisson distribution to account for over-dispersion leads to an overestimation of the QTL number and hence strongly discourages its application for identifying factors influencing count data. The proposed method is used to analyze the mice gallstone data of Lyons et al. (2003). Our results suggest the existence of a novel QTL on chromosome 4 interacting with another QTL previously identified on chromosome 5. We provide the corresponding code in R.

Keywords: quantitative trait loci; count data; model selection criteria; zero inflated Poisson regression

About the article

Published Online: 2010-06-22

Citation Information: Statistical Applications in Genetics and Molecular Biology, ISSN (Online) 1544-6115, DOI: https://doi.org/10.2202/1544-6115.1545. Export Citation

Comments (0)

Please log in or register to comment.
Log in