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Abstract Details
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Activity Number:
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631
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Type:
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Invited
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Date/Time:
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Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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ENAR
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| Abstract - #303908 |
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Title:
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Summarizing and Correcting the GC Content Bias in High-Throughput Sequencing
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Author(s):
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Yuval Benjamini*+ and Terence P Speed
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Companies:
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University of California at Berkeley and Walter and Eliza Hall Institute
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Address:
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Dept of Statistics, Albany, CA, 94706, United States
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Keywords:
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Sequencing ;
RNA-seq ;
GC bias ;
Poisson Process
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Abstract:
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Technical biases in high throughput sequencing can sometimes dominate the signal of interest. In particular, the GC content of the a genomic region (the number of G+C bases) can greatly impact the number of reads mapped to the region. This bias is not linear, and to make matters worse, its shape is not consistent from sample to sample. In this talk we describe a model for the GC effect developed on DNA sequencing, and discuss how the model can be estimated and the bias removed even when the signal is highly heterogeneous. We will discuss potential implications to RNA-seq assays.
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Authors who are presenting talks have a * after their name.
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