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Open Access Highly Accessed Methodology article

Profile analysis and prediction of tissue-specific CpG island methylation classes

Christopher Previti14, Oscar Harari2, Igor Zwir23 and Coral del Val12*

Author Affiliations

1 Department of Molecular Biophysics, DKFZ, German Cancer Research Center, Heidelberg, Germany

2 Department of Computer Science and Artificial Intelligence, CITIC-UGR (Research Center on Information and Comunication Technology), University of Granada, Granada, 18071, Spain

3 Department of Molecular Microbiology, Howard Hughes Medical Institute, Washington University School of Medicine, St Louis, MO, USA

4 Computational Biology Unit, Bergen Center for Computational Science, Sars Centre for Marine Molecular Biology, University of Bergen, Bergen, Norway

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BMC Bioinformatics 2009, 10:116  doi:10.1186/1471-2105-10-116

Published: 21 April 2009

Additional files

Additional file 1:

CGI dataset. This Excel table contains the CGI dataset that formed the foundation for our data-mining approach, as well as the classification of each CGI in the binary and tissue-specific methylation classes.

Format: XLS Size: 859KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 2:

Results of the Principle Component Analysis. This Excel table contains the Eigenvector plots of the PCA that were used to measure the contribution of each attribute to the principal components as well as the principle components themselves.

Format: XLS Size: 26KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 3:

Table of significant cluster intersections. This table shows the significant cluster intersections, ordered by size (#CGIs) and significance of each intersecting cluster (PI). Each cluster is identified by the data used in the clustering (Attribute or Methylation data) followed by the overall number of clusters, the clustering method (Hierarchical or K-means clustering) and the particular cluster used.

Format: DOC Size: 76KB Download file

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Additional file 4:

Decision tree. This Figure shows the decision tree used to predict the four CGI methylation classes.

Format: PNG Size: 665KB Download file

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Additional file 5:

Distribution of HCNE-overlapping PBCs over the gene association classes. Absolute number and percentage of CGIs in each PBC and gene-association class that overlap with a HCNE. A total of 3 conflicting CGIs that were determined to contain CDS but were part of a HCNE were excluded. Significant enrichment (p-value < 0.05) of methylation classes with HCNEs is marked bold and was determined via the Fisher exact test in conjunction with Bonferroni correction for multiple testing.

Format: DOC Size: 55KB Download file

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Additional file 6:

Table of variable correlation. Correlation analysis of all attributes shows that each relevant attribute was not replaceable by any other.

Format: XLS Size: 54KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data