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Open Access Research article

Integrative analysis of single nucleotide polymorphisms and gene expression efficiently distinguishes samples from closely related ethnic populations

Hsin-Chou Yang1*, Pei-Li Wang1, Chien-Wei Lin1, Chien-Hsiun Chen2 and Chun-Houh Chen1

Author Affiliations

1 Institute of Statistical Science, Academia Sinica, 128, Academia Road, Section 2 Nankang, Taipei 115, Taiwan

2 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan

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BMC Genomics 2012, 13:346  doi:10.1186/1471-2164-13-346

Published: 28 July 2012

Additional files

Additional file 1 :

Table S1. The total numbers of SNP and GE markers remaining in the analysis after quality control. This table summarizes the number of SNP and GE markers in each analysis of the eight combinations of ethnic populations. After quality control, 18,807 GE markers, 403,067 – 486,092 SNPs in the Affymetrix Human Mapping 500 K set, and 700,682 – 868,434 SNPs in the Affymetrix Array 6.0 set remained. The number of SNPs in the intersection of the Affymetrix Human Mapping 500 K and Array 6.0 sets was 385,493 – 469,057.

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Additional file 2 :

Figure S1. Classification of HapMap samples using whole-genome SNPs of Affymetrix Human Mapping 500 K set. All samples were superimposed onto a two-dimensional plane in an allele frequency (AF) biplot. (A) CHB, JPT, CEU, and YRI, (B) CHB and JPT, (C) CHB and YRI, (D) CHB and CEU, (E) JPT and YRI, (F) JPT and CEU, and (G) YRI and CEU. Red line with a B symbol indicates CHB samples; blue line with a J symbol indicates JPT samples; gray line with a Y symbol indicates YRI samples; green line with an E symbol indicates CEU samples.

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Additional file 3 :

Table S2. The best classification models. This table summarizes the key predictive markers, testing accuracy, cross-validation consistency (CVC), and number of genetic markers in the best classification models in the analysis of each of the eight combinations of ethnic populations.

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Additional file 4 :

Table S3. Genotype frequencies of key predictive SNPs in the best model for the classification of samples from ethnically distant populations. This table summarizes genotype frequencies of the key predictive SNPs in the 500 K-only (first field), Array6.0-only (second field), 500 K + GE (third field) and Array6.0 + GE (fourth field) analyses for the classification of samples from “CHB and YRI” (first panel), “CHB and CEU” (second panel), “JPT and YRI” (third panel), “JPT and CEU” (fourth panel), and “YRI and CEU” (fifth panel). The genotype frequencies also are shown in Figure 5.

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Additional file 5 :

Figure S2. Interface of BIASLESS software. BIASLESS software programmed in R and R-GUI is a user-friendly tool for the identification of key predictive markers to classify samples from different populations/groups.

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Additional file 6 :

Figure S3. Graphical outputs in BIASLESS software. BIASLESS software outputs six graphs including (A) overlay line graph, (B) parallel coordinates plot, (C) multidimensional scaling plot, (D) stacked-bar/box-whisker plot, (E) sample misclassification plot, and (F) marker impact plot from the analysis of a test example (Detailed explanations to these graphs can be seen in the User Guide of BIASLESS, which can be downloaded at http://www.stat.sinica.edu.tw/hsinchou/genetics/prediction/BIASLESS.htm webcite).

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