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Open Access Highly Accessed Methodology article

Copy number variation signature to predict human ancestry

Melissa Pronold12, Marzieh Vali1, Roger Pique-Regi3 and Shahab Asgharzadeh1*

Author Affiliations

1 Department of Pediatrics, Children’s Hospital Los Angeles and The Saban Research Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

2 Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

3 Department of Clinical and Translational Science, School of Medicine, Wayne State University, Detroit, MI, USA

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BMC Bioinformatics 2012, 13:336  doi:10.1186/1471-2105-13-336

Published: 27 December 2012

Additional files

Additional file 1:

Table S1. CNVs identified in individual samples.

Format: XLSX Size: 332KB Download file

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Additional file 2:

Table S2.Detailed list of the 73 caCNV signature.

Format: XLS Size: 54KB Download file

This file can be viewed with: Microsoft Excel Viewer

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Additional file 3:

Figure S1. Accuracy of Ancestry Prediction in Test Set using PCA of Genome-Wide SNPs. A) Scatter plot of the top two principal components using data generated from 4,326 genome-wide SNPs selected as ancestry informative markers (AIMs) shows separation of 100 European, 100 African-American, and 100 Han Chinese test samples based on self-reported ancestry (red square: European; yellow triangle: African-American; blue circle: Han Chinese). B) Scatter plot of ancestry estimates using SNPs versus caCNV signature in Africans (R2 = 0.914), C) Europeans (R2 = 0.924), and D) Han Chinese (R2 = 0.974).

Format: TIFF Size: 397KB Download file

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