Ameet Talwalkar, University of California, Berkeley
Friday, May 10, 2013, 12:00 PM to 1:30 PM
Location: 599 Engineering 2
Hosted By David Haussler, Biomolecular Engineering
Abstract:
Next-generation sequencing holds the promise for great advances in science and medicine, and computational methods are essential to extract actionable information from raw sequencing data. Unfortunately, computational tools developed to call variants from human sequencing data disagree on many of their predictions, and current methods to evaluate performance are ad-hoc and incomplete. A standardized methodology for benchmarking variant calling methods is thus required to stimulate development of genomic processing tools and facilitate communication among researchers. We propose such a benchmarking methodology (called SMASH). We generate synthetic datasets, organize and interpret a wide range of existing benchmarking data for real genomes, and propose a set of metrics for evaluation on this benchmarking data. Moreover, we illustrate the utility of SMASH to evaluate the performance of some leading SNP and structural variant calling algorithms.
Source: http://cbse.soe.ucsc.edu/events/event/2617
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