Using Trawler-standalone to discover overrepresented motifs in DNA and RNA sequences derived from various experiments including chromatin immunoprecipitation

Yannick Haudry, Mirana Ramialison, Benedict Paten, Joachim Wittbrodt, Laurence Ettwiller

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

Genome-wide location analysis has become a standard technology to unravel gene regulation networks. The accurate characterization of nucleotide signatures in sequences is key to uncovering the regulatory logic but remains a computational challenge. This protocol describes how to best characterize these signatures (motifs) using the new standalone version of Trawler, which was designed and optimized to analyze chromatin immunoprecipitation (ChIP) data sets. In particular, we describe the three main steps of Trawler-standalone (motif discovery, clustering and visualization) and discuss the appropriate parameters to be used in each step depending on the data set and the biological questions addressed. Compared to five other motif discovery programs, Trawler-standalone is in most cases the fastest algorithm to accurately predict the correct motifs especially for large data sets. Its running time ranges within few seconds to several minutes, depending on the size of the data set and the parameters used. This protocol is best suited for bioinformaticians seeking to use Trawler-standalone in a high-throughput manner. 

Original languageEnglish
Pages (from-to)323-334
Number of pages12
JournalNature Protocols
Volume5
Issue number2
DOIs
Publication statusPublished - Feb 2010
Externally publishedYes

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