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Activity Number:
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166
- Non-Clinical Statistics, Personalized Medicine, and Other Topics
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Type:
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Contributed
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Date/Time:
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Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Biopharmaceutical Section
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Abstract #317907
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Title:
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Finding Associations in a Heterogeneous Setting: Novel Statistical Test for Aberration Enrichment. The Signal Is in the Tails
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Author(s):
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Mohamed Aziz Mezlini*
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Companies:
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Evidation Health Inc, University of Toronto, Harvard Medical school
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Keywords:
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Novel statistical test;
Heterogeneous treatment effects;
HTE;
The signal is in the tails;
Clinical trials;
Omics
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Abstract:
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Most two-group statistical tests are implicitly looking for a broad pattern such as an overall shift in average between the two groups. Therefore, they operate best in settings where the effect of interest is uniformly affecting everyone in one group versus the other. In real-world applications, there are many scenarios where the effect of interest is heterogeneous. For example, a drug that works very well on only a proportion of patients and is equivalent to a placebo on the remaining patients, or a disease associated gene expression dysregulation that only occurs in a proportion of cases whereas the remaining cases have expression levels indistinguishable from the controls for the considered gene. In these examples with heterogeneous effects, we believe that using classical two-group statistical tests may not be the most powerful way to detect the signal. We developed a novel statistical test targeting heterogeneous effects. Our test demonstrated superior power in simulations as well as in several real datasets including clinical trials datasets and omics datasets such as gene expression, miRNA expression and DNA methylation datasets.
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Authors who are presenting talks have a * after their name.
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