A NESTED UNSUPERVISED APPROACH TO IDENTIFYING NOVEL MOLECULAR SUBTYPES. ELIZABETH GARRETT-MAYER ONCOLOGY BIOSTATISTICS JOHNS HOPKINS UNIVERSITY "MCMSki": The Past, Present, and Future of Gibbs Sampling Bormio, Italy January 12-14, 2005. INTRODUCTION: MOLECULAR SUBTYPING IN LUNG CANCER.
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JOHNS HOPKINS UNIVERSITY
"MCMSki": The Past, Present, and Future of Gibbs Sampling
January 12-14, 2005
Gene A Gene B Gene C
Profile 1 -1 -1 -1
Profile 2 -1 -1 0
Profile 3 -1 -11
Profile 4 . . .
. . . .
. . . .
. . . .
Profile 26 1 1 0
Profile 27 1 1 1
where -1 = underexpressed
0 = “normally” expressed
1 = overexpressed
The proportion of underexpressed and overexpressed samples
for each gene g are defined by:
Variation across samples (population variation)
Each data point, agt, is transformed to the POE scale
BRCA1 (breast cancer 1): tumor suppressor gene related to familial breast/ovarian cancer and other cancers
MEIS1 (myeloid ecotropic viral integration): transcription factor related to oncogenesis
FGF7 (fibroblast growth factor 7): related to lung development
Garrett, E.S., Parmigiani, G. A nested unsupervised approach to identifying novel molecular subtypes. Bernoulli, 10(6), 2004.
Garrett, E.S., Parmigiani, G. POE: Statistical Methods for Qualitative Analysis of Gene Expression. In The Analysis of Gene Expression Data: Methods and Software (eds. G. Parmigiani, E.S. Garrett, R.A. Irizarry, S.L. Zeger) Chapter 16, Springer: New York, 2003.
Parmigiani, G., Garrett, E., Anbazhagan, R., Gabrielson, E. A Statistical Framework forExpression-Based Molecular Classification in Cancer. Journal of Royal Statistical Society, Series B, with discussion, 64: 717-736, 2002.
Scharpf, R., Garrett, E.S., Hu, J., Parmigiani, G. Statistical Modeling and Visualization of Molecular Profiles in Cancer. Biotechniques, 34: S22-S29, 2003.ACKNOWLEDGEMENTS AND REFERENCES