TGS - BIOINFORMATICS APPLICATIONS NOTE Genome analysis Vol....

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Vol. 23 no. 15 2007, pages 2013–2014 BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btm282 Genome analysis Tree Gibbs Sampler: identifying conserved motifs without aligning orthologous sequences Xiaohui Cai 1,2 , Haiyan Hu 2 and Xiaoman Shawn Li 1,2, * 1 Division of Biostatistics and 2 Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, 410 West 10th Street, Indianapolis, IN 46202, USA Received on February 3, 2007; revised on April 17, 2007; accepted on May 18, 2007 Advance Access publication May 31, 2007 Associate Editor: Alfonso Valencia ABSTRACT Summary: Tree Gibbs Sampler is a software for identifying motifs by simultaneously using the motif overrepresentation property and the motif evolutionary conservation property. It identifies motifs without depending on pre-aligned orthologous sequences, which makes it useful for the extraction of regulatory elements in multiple genomes of both closely related and distant species. Availability: The Tree Gibbs Sampler software is freely down- loadable at https://compbio.iupui.edu/xiaomanli/LiSoftware/retrieve. php? ID ¼ tgs Contact: shawnli@iupui.edu 1 INTRODUCTION A transcription factor can bind to short DNA segments in the regulatory regions of many different genes to control their expression. The common pattern of these short DNA segments bound by a transcription factor is called a motif. Recently, many computational methods have been developed to identify motifs by finding overrepresented and conserved DNA segments (putative motif instances) in the regulatory regions of a set of candidate genes in multiple related species (Liu, 2004; Moses, 2004; Prakash, 2004, 2005; Sinha, 2004; Wang, 2003). Most of these methods align orthologous sequences first and then identify motifs from the aligned orthologous sequences, often without taking the species divergent time into account. However, motif instances are not always aligned with their counterpart motif instances in the multiple alignments of orthologous sequences (Li, 2005). Moreover, without taking the divergent time into account, one often cannot distinguish the conserved segments due to the short divergent time from the conserved segments due to the functionality. Here we developed a useful software, Tree Gibbs Sampler (TGS), which identifies motifs from unaligned orthologous sequences by taking the divergent time into account properly. 2 SOFTWARE
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TGS - BIOINFORMATICS APPLICATIONS NOTE Genome analysis Vol....

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