Record Details

Detecting Differential Gene Expression in Subgroups of a Disease Population

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Field Value
Title Detecting Differential Gene Expression in Subgroups of a Disease Population
Names Emerson, Sarah C. (creator)
Emerson, Scott S. (creator)
Date Issued 2013-09-18 (iso8601)
Note This is the publisher’s final pdf. The published article is copyrighted by Walter de Gruyter GmbH and can be found at: http://www.degruyter.com/view/j/ijb.
Abstract In many disease settings, it is likely that only a subset of the disease population will exhibit
certain genetic or phenotypic differences from the healthy population. Therefore, when seeking to identify
genes or other explanatory factors that might be related to the disease state, we might expect a mixture
distribution of the variable of interest in the disease group. A number of methods have been proposed for
performing tests to identify situations for which only a subgroup of samples or patients exhibit differential
expression levels. Our discussion here focuses on how inattention to standard statistical theory can lead to
approaches that exhibit some serious drawbacks. We present and discuss several approaches motivated by
theoretical derivations and compare to an ad hoc approach based upon identification of outliers. We find
that the outlier-sum statistic proposed by Tibshirani and Hastie offers little benefit over a t-test even in the
most idealized scenarios and suffers from a number of limitations including difficulty of calibration, lack of
robustness to underlying distributions, high false positive rates owing to its asymmetric treatment of
groups, and poor power or discriminatory ability under many alternatives.
Genre Article
Topic efficiency
Identifier Emerson, S. C., & Emerson, S. S. (2013). Detecting differential gene expression in subgroups of a disease population. International Journal of Biostatistics, 9(1), 95-108. doi:10.1515/ijb-2013-0010

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