PCAN: Probabilistic correlation analysis of two non‐normal data sets

Author:

Zoh Roger S.1,Mallick Bani2,Ivanov Ivan3,Baladandayuthapani Veera4,Manyam Ganiraju4,Chapkin Robert S.5,Lampe Johanna W.6,Carroll Raymond J.2

Affiliation:

1. Department of Epidemiology and Biostatistics, Texas A&M University, College Station Texas, U.S.A.

2. Department of Statistics, Texas A&M University College Station, Texas, U.S.A.

3. Department of Veterinary Medicine and Biomedical Sciences, Texas A&M University Texas, U.S.A.

4. The University of Texas MD Anderson Cancer Center 1515 Holcombe Blvd, Houston, Texas, U.S.A.

5. Program in Integrative Nutrition and Complex Diseases, Texas A&M University Texas, U.S.A.

6. Department of Epidemiology, University of Washington and the Fred Hutchinson Cancer Research Center Seattle Washington, U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Reference32 articles.

1. Differential expression analysis for sequence count data

2. Archambeau C. andBach F.(2009). Sparse Probabilistic Projections. In Advances in Neural Information Processing Systems 21 22nd Annual Conference on Neural Information Processing Systems 2008 (pp. 73‐80). NY: Curran Associates Inc. Red Hook.

3. Bach F. R.andJordan M. I.(2006). A probability interpretation of canonical correlation analysis. Technical Report 688.

4. Bishop C. M.(2007).Pattern Recognition and Machine Learning (Information Science and Statistics). New York NY: Springer 1 edition.

5. Congdon P.(2006).Bayesian Statistical Modelling. West Sussex England: John Wiley & Sons 2 edition.

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