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Activity Number:
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142
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Type:
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Invited
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Date/Time:
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Monday, August 1, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Genomics and Genetics
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Abstract #318050
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Title:
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Overcoming Bias and Batch Effects in RNAseq Data
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Author(s):
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Michael I. Love and Rafael A. Irizarry*
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Companies:
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Harvard T.H. Chan School of Public Health and Dana-Farber Cancer Institute
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Keywords:
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Genomics ;
RNA-Seq
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Abstract:
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In this talk I will demonstrate the presence of bias, systematic error and unwanted variability in next generation sequencing. I will show the substantial downstream effects these have on downstream results and how they can lead to misleading biological conclusions. I will do this using data from the public repositories as well as our own. We will then describe some preliminary solutions to these problems.
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Authors who are presenting talks have a * after their name.
