Home » Statistical and Computational Challenges in Next-Generation Sequencing
Statistical and Computational Challenges in Next-Generation Sequencing
October 10, 2008
Sandrine Dudoit, Terry Speed, Margaret Taub
No Speakers Assigned Yet.
For the past decade, microarrays have been the assays of choice for high-throughput studies of gene expression. Recent improvements in the efficiency, quality, and cost of genome-wide sequencing are prompting biologists to rapidly abandon microarrays in favor of so-called next-generation sequencers, e.g., Applied Biosystems' SOLiD, Helicos BioSciences' HeliScope, Illumina's Solexa, and Roche's 454 Life Sciences sequencing systems. These high-throughput sequencing technologies have already been applied for studying genome-wide transcription levels (mRNA-Seq), transcription factor binding sites (ChIP-Seq), chromatin structure, and DNA methylation status. While sequencing-based gene expression studies have been touted as overcoming longstanding limitations of microarray-based studies, these new biotechnologies raise similar as well as novel statistical and computational challenges.
This workshop's website is at: http://www.stat.berkeley.edu/~seqmtg/