This article is part of the supplement: The 2010 International Conference on Bioinformatics and Computational Biology (BIOCOMP 2010): Genomics

Open Access Research article

Maximum predictive power of the microarray-based models for clinical outcomes is limited by correlation between endpoint and gene expression profile

Chen Zhao1, Leming Shi2, Weida Tong2, John D Shaughnessy3, André Oberthuer4, Lajos Pusztai5, Youping Deng6, W Fraser Symmans5 and Tieliu Shi1*

Author Affiliations

1 The Center for Bioinformatics and The institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, 200241, China

2 National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA

3 Laboratory of Myeloma Genetics, Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA

4 MD, Children's Hospital, Department of Pediatric Oncology and Hematology, University of Cologne, Kerpener Strasse 62, D-50924 Cologne, Germany

5 Department of Breast Medical Oncology and Department of Pathology, The University of Texas M.D. Anderson Cancer Center, Unit 1354, PO Box 301439, Houston, TX 77230-1439, USA

6 Rush University Cancer Center, Department of Internal Medicine, Rush University Medical Center, Chicago, IL 60612, USA

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BMC Genomics 2011, 12(Suppl 5):S3  doi:10.1186/1471-2164-12-S5-S3

Published: 23 December 2011

Additional files

Additional file 1:

Algorithm of the consistency degree.

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Additional file 2:

Performances of the candidate models in MAQC external validation.

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Additional file 3:

MCCs and the corresponding consistency degrees.

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Additional file 4:

Change Point Redefined Classification Endpoints.

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Additional file 5:

Prediction error sample list.

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