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Abstract Details
Activity Number:
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337
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #301841 |
Title:
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Statistical Methods for Analysis of Pooled Sequencing Data
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Author(s):
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Zhi Wei*+
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Companies:
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New Jersey Institute of Technology
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Address:
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GITC 4400, Department of Computer Science, Newark, NJ, 07102,
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Keywords:
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next-generation sequencing ;
pooled sequencing
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Abstract:
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Although the development of next-generation sequencing technologies (NGS) in the past few years has made the cost of DNA sequencing plummet dramatically, it is still prohibitively expensive to sequence the complete genomes of hundreds of individuals. Just as in pre-GWAS, re-sequencing small targeted genomic regions is now routinely to harness the massive capacity of NGS. Pooled sequencing is used to identify rare variants in targeted regions of the genome in large populations. However, detection of rare variants from pooled sequencing is more challenging than from individual sequencing. Here we propose a new statistical procedure to detect genomic variants from the output of pooled sequencing data. Simulations and analysis of real data will be used to demonstrate the merits of our approach in comparison with existing methods.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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