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Abstract Details
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Activity Number:
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559
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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IMS
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| Abstract - #305708 |
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Title:
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Base Calling and SNP Calling on Next-Generation Sequencing Data
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Author(s):
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Xinping Cui*+ and Gabriel Murillo and Ping Ma and Na You
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Companies:
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University of California at Riverside and University of California at Riverside and University of Illinois at Urbana-Champaign and Sun Yat-Sen University
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Address:
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1338 Olmsted Hall , Riverside, CA, , USA
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Keywords:
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next generation sequencing ;
base calling ;
SNP calling ;
random-effect-multivariate-mixture model
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Abstract:
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Recent advances in next-generation sequencing (NGS) technology now provide the potential to detect all single nucleotide polymorphisms (SNPs) including rare ones in a genomic region. The power of NGS based SNP detection is critically dependent upon the accuracy of base calling. In this talk, I will first discuss our recently developed base calling algorithm that was built on random-effect-multivariate-mixture-model. I will then discuss our new likelihood based SNP caller, Genotype Model Selection (GeMS), which accounts for genomic sample preparation errors as well as base-calling and alignment errors. We will demonstrate that the proposed base caller and SNP caller result in a significant improve in the power of SNP detection.
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Authors who are presenting talks have a * after their name.
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