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This article is part of the supplement: Genetic Analysis Workshop 18: Human sequence data in extended pedigrees

Open Access Correction

Correction: A dual clustering framework for association screening with whole genome sequencing data and longitudinal traits

Ying Liu1, Chien Hsun Huang1, Inchi Hu2, Shaw-Hwa Lo1 and Tian Zheng1*

Author Affiliations

1 Department of Statistics, Columbia University, New York, NY 10027, USA

2 ISOM, Hong Kong University of Science and Technology, Kowloon, Hong Kong

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BMC Proceedings 2014, 8(Suppl 1):S112  doi:10.1186/1753-6561-8-S1-S112

The electronic version of this article is the complete one and can be found online at:

Published:24 July 2014

© 2014 Liu et al.; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.


For the previous publication of our article [1], Figure 1 was incorrectly processed as grayscale. We present, here in this correction, the original Figure in full color.

thumbnailFigure 1. Clustering of individuals using SNPs with MAFs between 0.01 and 0.05 for MAP4. A, Shown are 10 clusters, with the numbers at the top odds ratios within each partition block based on blood pressures. Each row is a SNP, and each column is an individual. SNPs are ordered with decreasing MAFs (from top to bottom). Green vertical bars indicate subjects with higher blood pressures (see text). Genotype aa is plotted in red, aA is plotted in blue, and AA is plotted in white (a denotes the minor allele). The partitions of the 849 individuals are indicated by dotted lines. Most partition elements are driven by similarity on rarer SNPs but not on more common SNPs. B, Clustering of individuals using their SBP curves from the first simulation. It can be seen that individuals are reasonably grouped into 1 high blood pressure cluster and 1 low blood pressure cluster.

This article has been published as part of BMC Proceedings Volume 8 Supplement 1, 2014: Genetic Analysis Workshop 18. The full contents of the supplement are available online at


  1. Liu Y, Huang CH, Hu I, Lo SH, Zheng T: A dual clustering framework for association screening with whole genome sequencing data and longitudinal traits.

    BMC Proc 2014, 8(Suppl 1):S47. BioMed Central Full Text OpenURL