Outlier sums for differential gene expression analysis
Open Access
- 15 May 2006
- journal article
- research article
- Published by Oxford University Press (OUP) in Biostatistics
- Vol. 8 (1), 2-8
- https://doi.org/10.1093/biostatistics/kxl005
Abstract
We propose a method for detecting genes that, in a disease group, exhibit unusually high gene expression in some but not all samples. This can be particularly useful in cancer studies, where mutations that can amplify or turn off gene expression often occur in only a minority of samples. In real and simulated examples, the new method often exhibits lower false discovery rates than simple t-statistic thresholding. We also compare our approach to the recent cancer profile outlier analysis proposal of Tomlins and others (2005).Keywords
This publication has 3 references indexed in Scilit:
- Microarray data analysis: from disarray to consolidation and consensusNature Reviews Genetics, 2006
- Recurrent Fusion of TMPRSS2 and ETS Transcription Factor Genes in Prostate CancerScience, 2005
- Significance analysis of microarrays applied to the ionizing radiation responseProceedings of the National Academy of Sciences of the United States of America, 2001