Kakushadze Zura, Yu Willie
Quantigic® Solutions LLC, 1127 High Ridge Road #135, Stamford, CT 06905, United States.
Free University of Tbilisi, Business School & School of Physics, 240, David Agmashenebeli Alley, Tbilisi 0159, Georgia.
Biomol Detect Quantif. 2017 Aug 2;13:7-31. doi: 10.1016/j.bdq.2017.07.001. eCollection 2017 Sep.
We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.
