Open Access Research article

An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer

Jaesik Jeong1, Lang Li2, Yunlong Liu2, Kenneth P Nephew3, Tim Hui-Ming Huang4 and Changyu Shen1*

Author Affiliations

1 Department of Medicine/Division of Biostatistics, Indiana University, Indianapolis, IN, USA

2 Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA

3 Department of Medical Science/Simon Cancer Center, Indiana University, Bloomington, IN, USA

4 Department of Molecular Virology, Immunology and Medical Genetics/Human Cancer Genetics, The Ohio State University, Columbus, OH, USA

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BMC Medical Genomics 2010, 3:55  doi:10.1186/1755-8794-3-55

Published: 25 November 2010

Additional files

Additional file 1:

Table S1 -- Gene expression data structure. This table shows the gene expression data structure in both group: wild type and antiestrogen resistant group.

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Additional file 2:

Table S2 -- Gene lists which are hypomethylated and up-regulated. This table presents gene lists obtained by using three different cutoff values with the OHT data set.

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Additional file 3:

Figure S1 -- Venn diagram presenting gene overlap. Each figure is obtained using three different cutoff values. Based on each cutoff values, the status of each gene is determined in both data sets. The number of gene overlaps which were obtained by using gene expression data in both data set is calculated. The numbers in each Venn diagram presents the number of common genes in both data sets.

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Additional file 4:

Figure S2 -- Histogram of residuals. This histogram is based on standardized residuals obtained by using estimates in our model; Top: residuals histogram of gene expression in ICI; Bottom: residuals histogram of methylation in ICI.

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Additional file 5:

Figure S3 -- Q-Q plot of residuals. Each Q-Q plot is based on standardized residuals obtained by using parameter estimates in our model in ICI; Left: this plot is obtained by using gene expression residuals; Right: this plot is obtained by using methylation residuals.

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Additional file 6:

Figure S4 -- Histogram of gene effect. Each histogram is based on estimated gene effect in our model in ICI; Top: these plots are obtained by using estimated gene effect of each group in gene expression (Left:WT and Right:ICI); Bottom: these plots are obtained by using estimated gene effect of each group in methylation (Left:WT and Right:ICI).

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Additional file 7:

Figure S5 -- Q-Q plot of gene effect. Each Q-Q plot is based on estimated gene effect in our model in ICI; Top: these plots are obtained by using estimated gene effect of each group in gene expression (Left:WT and Right:ICI); Bottom: these plots are obtained by using estimated gene effect of each group in methylation (Left:WT and Right:ICI).

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Additional file 8:

Figure S6 -- Histogram of added probe effect. Each histogram is based on estimated probe effect in our model in ICI; Left: these plots are obtained by using estimated added probe effect in gene expression; Right: these plots are obtained by using estimated added probe effect in methylation.

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Additional file 9:

Figure S7 -- Q-Q plot of added probe effect. Each Q-Q plot is based on estimated probe effect in our model in ICI; Left: these plots are obtained by using estimated added probe effect in gene expression; Right: these plots are obtained by using estimated added probe effect in methylation.

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Additional file 10:

Supplementary materials -- Details about modeling and estimation. This file includes details about marginal modeling and parameter estimation. Also, the exact form of parameter estimators are given.

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