Login to MyKarger

New to MyKarger? Click here to sign up.

Login with Facebook

Forgot Password? Reset your password

Authors, Editors, Reviewers

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

Submission Websites List

Institutional Login (Shibboleth)

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

Table of Contents
Vol. 73, No. 3, 2012
Issue release date: July 2012
Section title: Original Paper
Hum Hered 2012;73:148–158

Detecting Rare Variants for Quantitative Traits Using Nuclear Families

Guo W.a, b · Shugart Y.Y.a
aDivision of Intramural Division Program, National Institute of Mental Health, National Institute of Health, Bethesda, Md., USA; bKey Laboratory for Applied Statistics of Ministry of Education and School of Mathematics and Statistics, Northeast Normal University, Changchun, China
email Corresponding Author

Yin Yao Shugart

Division of Intramural Research Program, National Institute of Mental Health National Institute of Health, Building 35, Room 3A 1000, 35 Convent Drive

Bethesda, MD 20892 (USA)

Tel. +1 301 496 4341, E-Mail kay1yao@mail.nih.gov

Do you have an account?

Login Information

Contact Information

I have read the Karger Terms and Conditions and agree.


With the advent of sequencing technology opening up a new era of personal genome sequencing, huge amounts of rare variant data have suddenly become available to researchers seeking genetic variants related to human complex disorders. There is an urgent need for the development of novel statistical methods to analyze rare variants in a statistically powerful manner. While a number of statistical tests have already been developed to analyze collapsed rare variants identified by association tests in case-control studies, to date, only two FBAT tests-for-rare (described in the updated FBAT version v2.0.4) have applied collapsing methods analogously in family-based designs. For further research in this area, this study aims to introduce three new beta-determined weight tests for detecting rare variants for quantitative traits in nuclear families. In addition to evaluating the performance of these new methods, it also evaluates that of the two FBAT tests-for-rare, using extensive simulations of situations with and without linkage disequilibrium. Results from these simulations suggest that the four tests using beta-determined weights outperform the two collapsing methods used in FBAT (-v0 and -v1). In addition, both the linear combination method (detailed in the FBAT menu v2.0.4) and the multiple regression method (mixing LASSO and Ridge penalties) performed better than the other two beta-determined weight tests we proposed. Following testing and evaluation, we submitted four new beta-determined weight methods of statistical analysis in a computer program to the Comprehensive R Archive Network (CRAN) for general use.

© 2012 S. Karger AG, Basel

Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: December 08, 2011
Accepted: March 30, 2012
Published online: June 12, 2012
Issue release date: July 2012

Number of Print Pages: 11
Number of Figures: 1
Number of Tables: 3

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 or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
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.