Research article
Early detection of breast cancer based on gene-expression patterns in peripheral blood cells
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* Corresponding author: Praveen Sharma praveen.sharma@diagenic.com
1 DiaGenic ASA, Oslo, Norway
2 Departments of Health, Research and Policy, and Statistics, Stanford University, Stanford, CA, USA
3 Department of Radiology, Ullevål University Hospital, Oslo, Norway
4 Department of Clinical Chemistry, Ullevål University Hospital, Oslo, Norway
5 Department of Pathology, The Gade Institute, Haukeland University Hospital, Norway
6 Department of Pathology, Ullevål University Hospital, Oslo, Norway
7 Department of Surgery, Ullevål University Hospital, Oslo, Norway
8 Department of Genetics, The Norwegian Radium Hospital; and University of Oslo, Faculty division, The Norwegian Radium Hospital, Oslo Norway
Breast Cancer Research 2005, 7:R634-R644 doi:10.1186/bcr1203
See related letter by Li at http://breast-cancer-research.com/content/7/5/E5
Published: 14 June 2005Additional files
Additional File 1:
Supplementary Figure 1, a pdf showing batch adjustment. (Left) Normalized data before batch adjustment; (right) normalized data after batch adjustment by ANOVA.
Format: PDF Size: 41KB Download file
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Additional File 2:
Supplementary Table 1, an Excel file showing the raw data for 1,368 genes. C, breast-cancer class; N, non-breast-cancer class.
Format: XLS Size: 4.8MB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional File 3:
Supplementary Table 2, an Excel file showing the batch-corrected data for 1,368 genes. C, breast-cancer class; N, non-breast-cancer class.
Format: XLS Size: 2.5MB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional File 4:
Supplementary Figure 2, pdf showing misclassification rate as a function of threshold value and the number of genes involved when the error is calculated by taking an average of the class probability for each sample in all 60 cross-validation segments. The upper graph shows that the minimum overall misclassification error is observed at a threshold value of 2.42. The lower graph shows the profile for the misclassification error for breast-cancer (C) and non-breast-cancer (N) samples as a function of threshold value and the number of genes involved.
Format: PDF Size: 44KB Download file
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Additional File 5:
Supplementary Figure 3, a pdf showing estimated cross-validated probabilities of 60 different blood samples. Red circles represent breast-cancer class (C) and green circles represent non-breast-cancer class (N). Each sample has two probabilities, one for the breast-cancer class and the other for the non-breast-cancer class. The sample is classified in the class whose probability is >0.5.
Format: PDF Size: 43KB Download file
This file can be viewed with: Adobe Acrobat Reader