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Abstract Details

Activity Number: 437
Type: Invited
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #303841
Title: Batch Effects from Biological and Technological Artifacts in High-Throughput Data Collections
Author(s): Jeffrey Leek*+
Companies: The Johns Hopkins University
Address: , Baltimore, MD, ,
Keywords: TCGA ; batch effects ; prediction ; sequencing ; microarray ; surrogate variable analysis
Abstract:

Batch effects are present in any large scale study in which all the samples cannot be collected and processed at a single time. In this talk we will examine the batch effects that have been detected in TCGA data and how to identify and adjust for their effects on analysis. We will show this problem is not exclusive to the TCGA data and affects nearly every high-throughput data analysis. We will show that "batch effects" may be due to both latent technological and biological variation. We will discuss appropriate batch correction for both prediction and epidemiological analysis. Though large data resources are becoming readily available it is important to be aware of their limitations and potential bias so that valid conclusions can be drawn.


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