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Abstract Details

Activity Number: 281
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #304149
Title: Development of Fast, Slim, and Accurate Amplicon Variant Detection Algorithm for Next-Generation Sequencing
Author(s): Wei-Min Liu*+ and Yan Li
Companies: Roche Molecular Systems, Inc. and Roche Molecular Systems, Inc.
Address: 4300 Hacienda Drive, Pleasanton, CA, 94588-2722, United States
Keywords: alignment ; cancer ; complex mutation ; next generation sequencing ; NGS ; sequencing

Amplicon variant detection (AVD) is one of the important applications for next generation sequencing (NGS). The enormous amount of sequencing data generated by the NGS technology necessitates the development of fast, slim and accurate AVD algorithm. Here, we present our approaches to develop and implement an AVD algorithm with fast processing speed and efficient use of memory space. The hash function and Burrows-Wheeler transformation are customized to speed up AVD so that processing the large amount of sequencing reads can be completed in a relative short time. We also propose a special way to compress the alignments of reads with reference sequences. Our format uses significantly smaller memory space in comparison with some widely used formats such as SAM/BAM. Moreover, it is useful to automatically identify whether the newly found variants exist in a public database such as COSM

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