Login to MyKarger

New to MyKarger? Click here to sign up.

Login with Facebook

Forgot your password?

Authors, Editors, Reviewers

For Manuscript Submission, Check or Review Login please go to Submission Websites List.

Submission Websites List

Institutional Login
(Shibboleth or Open Athens)

For the academic login, please select your country in the dropdown list. You will be redirected to verify your credentials.

Original Paper

Free Access

A Statistical Method for Identifying Trait-Associated Copy Number Variants

Jeng J.a · Wu Q.b · Li H.b

Author affiliations

aDepartment of Statistics, North Carolina State University, Raleigh, N.C., and bDepartment of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa., USA

Corresponding Author

Prof. Hongzhe Li, PhD

Department of Biostatistics and Epidemiology

University of Pennsylvania Perelman, School of Medicine

423 Guardian Drive, Philadelphia, PA 19104 (USA)

E-Mail hongzhe@upenn.edu

Related Articles for ""

Hum Hered 2015;79:147-156

Do you have an account?

Login Information

Contact Information

I have read the Karger Terms and Conditions and agree.


Copy number variants (CNVs), ranging in size from about one kilobase to several megabases, are DNA alterations of a genome that result in the cell having less or more than two copies of segments of the DNA. Such CNVs have been shown to be associated with many complex phenotypes, ranging from diseases to gene expressions. Novel methods have been developed for identifying CNVs both at the individual and at the population level. However, methods for testing CNV association are limited. Most available methods employ a two-step approach, where CNVs carried by the samples are identified first and then tested for association. However, the results of such tests depend on the threshold used for CNV identification and also the number of CNVs to be tested. We developed a method, CNVtest, to directly identify the trait-associated CNVs without the need of identifying sample-specific CNVs. We show that CNVtest asymptotically controls the type I error rate and identifies true trait-associated CNVs with a high probability. We demonstrate the methods using simulations and an application to identify the CNVs that are associated with population differentiation.

© 2015 S. Karger AG, Basel

Article / Publication Details

First-Page Preview
Abstract of Original Paper

Published online: July 28, 2015
Issue release date: July 2015

Number of Print Pages: 10
Number of Figures: 3
Number of Tables: 1

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE

Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.