Abstract
SAM is a computer package for correlating gene expression with an outcome parameter such as treatment, survival time, or diagnostic class. It thresholds an appropriate test statistic and reports the q-value of each test based on a set of sample permutations. SAM works as a Microsoft Excel add-in and has additional features for fold-change thresholding and block permutations. Here, we explain how the SAM methodology works in the context of a general approach to detecting differential gene expression in DNA microarrays. Some recently developed methodology for estimating false discovery rates and q-values has been included in the SAM software, which we summarize here.
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© 2003 Springer-Verlag New York, Inc.
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Storey, J.D., Tibshirani, R. (2003). SAM Thresholding and False Discovery Rates for Detecting Differential Gene Expression in DNA Microarrays. In: Parmigiani, G., Garrett, E.S., Irizarry, R.A., Zeger, S.L. (eds) The Analysis of Gene Expression Data. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/0-387-21679-0_12
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DOI: https://doi.org/10.1007/0-387-21679-0_12
Publisher Name: Springer, New York, NY
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