Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer

<table>Principal component analysis identity testing of a variety of normal SNP profiles from the germline DNA of prostate cancer patients (PC) used in the study compared to a set of HapMap normal reference populations from Nigeria (YRI), Europe (CEU), China (CHB), or, of African American (AFA) decent.  The <i>x</i> and <i>y</i> axes represent the 1st and 2nd eigenvectors.  </table>

Journal of Probability and Statistics

fig2

Figure 2

Figure 2: Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer 

Figure 2 | Clustering-Based Method for Developing a Genomic Copy Number Alteration Signature for Predicting the Metastatic Potential of Prostate Cancer 