RSAT: regulatory sequence analysis tools

By M. Thomas-Chollier, Olivier Sand, Jean-Valéry Turatsinze, Rekin's Janky, Matthieu Defrance, E. Vervisch, Sylvain Brohée, Jacques van Helden. Nucleic Acids Res., 2008

296 citations recorded by the source corpus.

The regulatory sequence analysis tools (RSAT, http://rsat.ulb.ac.be/rsat/) is a software suite that integrates a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. The suite includes programs for sequence retrieval, pattern discovery, phylogenetic footprint detection, pattern matching, genome scanning and feature map drawing. Random controls can be performed with random gene selections or by generating random sequences according to a variety of background models (Bernoulli, Markov). Beyond the original word-based pattern-discovery tools (oligo-analysis and dyad-analysis), we recently added a battery of tools for matrix-based detection of cis-acting elements, with some original features (adaptive background models, Markov-chain estimation of P-values) that do not exist in other matrix-based scanning tools. The web server offers an intuitive interface, where each program can be accessed either separately or connected to the other tools. In addition, the tools are now available as web services, enabling their integration in programmatic workflows. Genomes are regularly updated from various genome repositories (NCBI and EnsEMBL) and 682 organisms are currently supported. Since 1998, the tools have been used by several hundreds of researchers from all over the world. Several predictions made with RSAT were validated experimentally and published.

Subfields: Molecular Biology

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Citations in the corpus

EcoCyc: a comprehensive database of Escherichia coli biology (2010, methodology): “We curated and relocated the binding sites for CytR, OxyR, FhlA based on computational tools [RSAT (3)] that support the identification of overrepresented motifs in regulatory regions.”
The MEME Suite (2015, background): “Capability MEME Suite (17) Consensus (18) Gibbs Sampler (19) RSAT (20) Trawler (21) WChIPMotifs (22) MoDTools (23) YMF 3.”
Characterization of the CLEAR network reveals an integrated control of cellular clearance pathways. (2011, methodology): “org) and analyzed with the CLEAR PWM by using PatSer from the Regulatory Sequence Analysis Tool package with default parameters (86).”
Inferring direct DNA binding from ChIP-seq (2012, methodology): “The CentriMo algorithm resembles the earlier ‘position-analysis’ algorithm (29,30).”
RegulonDB version 7.0: transcriptional regulation of Escherichia coli K-12 integrated within genetic sensory response units (Gensor Units) (2010, methodology): “We measured the similarity distances between matrices with the program ‘compare-matrices’, which is included in the program suite RSA-tools (7), and we used as distance metric the ‘Normalized Correlation’.”