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Activity Number: 356
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #320851 View Presentation
Title: Power Analysis for RNA-Seq Differential Expression Studies
Author(s): Lianbo Yu* and Soledad Fernandez and Guy N. Brock
Companies: The Ohio State University and The Ohio State University and The Ohio State University
Keywords: Differential Expression ; Sample Size ; RNA-Seq ; Power

Sample size and power calculation are essential components of experimental designs in biomedical research. It is very challenging to estimate power for RNA-Seq differential expression under complex experimental designs. Moreover, the dependency among genes should be taken into account in order to obtain accurate results. Therefore, we propose a simulation based approach for power estimation using the negative binomial distribution and assuming a generalized linear model (at the gene level) that considers the dependence between the gene expression level and its variance (dispersion). We compare the performance of both LRT and Wald tests under different scenarios where the simulated exact distribution of the test statistics under the null hypothesis was used for false positive control.

Authors who are presenting talks have a * after their name.

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