Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Correction: Multiclass classification of microarray data with repeated measurements: application to cancer. | Correction Correction Multiclass classification of microarray data with repeated measurements application to cancer Ka Yee Yeung and Roger E. Bumgarner Address Department of Microbiology Box 358070 University of Washington Seattle WA 98195 USA. Correspondence Ka Yee Yeung. Email kayee@ Published 3 January 2006 Genome Biology 2005 6 405 doi gb-2005-6-13-405 The electronic version of this article is the complete one and can be found online at http 2005 6 13 405 2005 BioMed Central Ltd After the publication of this work 1 we discovered programming errors in our software implementation of the proposed error-weighted uncorrelated shrunken centroid EWUSC algorithm and the uncorrelated shrunken centroid USC algorithm. We have corrected these errors and the updated results are summarized in the revised Table 6. On the NCI 60 data both Figure 1 in 1 and the revised Figure 1 showed that USC generally produces higher prediction accuracy than the shrunken centroid algorithm SC 2 using the same number of relevant genes. Using the revised software implementation USC requires fewer 2 116 instead of 2 315 as reported in 1 genes to achieve 72 accuracy. The number of genes required by SC to achieve the same prediction accuracy remains the same 3 998 . Figure 2 shows the results of applying EWUSC to the training set four-fold cross-validation data and test set of the multiple tumor data over a range of shrinkage thresholds A and correlation thresholds p0 . The revised Figure 2 shows the same general trend as Figure 2 in 1 the percentage of errors is reduced when p0 1 over most values of A on the training set cross-validation data and test set Figure 2d shows that the number of relevant genes is drastically reduced when genes with correlation threshold above are removed. The values of the optimal shrinkage thresholds A determined from the cross-validation results have changed using the revised implementation. Specifically the optimal .
