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Activity Number: 370
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract #321256
Title: Selecting Covariates in Differential Expression Analysis of RNA-Seq Data
Author(s): Yet Nguyen* and Dan Nettleton
Companies: Iowa State University and Iowa State University
Keywords: RNA-seq ; FDR ; Backward Selection ; Forward Selection ; ShrinkBayes ; p-value

Differential expression analysis of RNA-seq can often be more challenged due to the presence of many covariates associated with experimental design, experimental units, RNA samples, etc. Ignoring relevant covariates or including irrelevant covariates can decrease the ability to detect differentially expressed genes. In this talk, we investigate the performance of backward selection and forward selection in an experiment that involves the measurement of transcript levels in blood samples taken from two lines of pigs that are divergently selected for residual feed intake. A simulation study shows advantages of backward selection and forward selection methods over the alternative approaches that either including or excluding all covariates.

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

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