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The Scientific World Journal
Volume 2014 (2014), Article ID 362141, 13 pages
http://dx.doi.org/10.1155/2014/362141
Research Article

RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes

School of Information Technology, Deakin University, 221 Burwood Highway, Melbourne, VIC 3125, Australia

Received 5 November 2013; Accepted 11 December 2013; Published 19 January 2014

Academic Editors: P. Chong and P. Van Dam

Copyright © 2014 Ashish Saini et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

The Supplementary Material consists of four files, including Tables S1, S2, and S3 and Figure S1. Table S1 shows the list of the genes in the gene signature constructed by the RRHGE algorithm. Tables S2 and S3 show the enriched gene ontology (GO) terms and the enriched pathways for the genes in the RRHGE gene signature, respectively, and show that the biological meaning of the RRHGE gene signature is significantly associated with cancers. At last, Figure S1 shows the heatmap of the RRHGE gene signature, which clearly shows the distinct gene expression patterns for the RRHGE gene signature in the ER+ and ER− breast cancer samples. These supplementary files further supports that the RRHGE gene signature has its advantage in classifying ER+ and ER- breast cancer patient samples effectively.

  1. Supplementary Material