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Updated: Jul 5, 2026

Introductory Analysis and Validation of CUT&RUN Sequencing Data
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Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

RSAT: regulatory sequence analysis tools.

Morgane Thomas-Chollier1, Olivier Sand, Jean-Valéry Turatsinze

  • 1Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, Campus Plaine, CP 263. Bld du Triomphe, B-1050 Bruxelles, Belgium.

Nucleic Acids Research
|May 23, 2008
PubMed
Summary
This summary is machine-generated.

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Regulatory Sequence Analysis Tools (RSAT) offers advanced software for detecting cis-regulatory elements in genomes. Its updated features enhance pattern discovery and matrix-based scanning for biological research.

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Identifying cis-regulatory elements is crucial for understanding gene regulation.
  • Existing tools may lack comprehensive features for motif discovery and analysis.
  • The Regulatory Sequence Analysis Tools (RSAT) suite provides a robust platform for genomic analysis.

Purpose of the Study:

  • To present the updated features and capabilities of the RSAT software suite.
  • To highlight RSAT's advancements in detecting cis-regulatory elements using both word-based and matrix-based methods.
  • To emphasize the accessibility and integration potential of RSAT through its web server and web services.

Main Methods:

  • RSAT integrates modular tools for sequence retrieval, pattern discovery (oligo- and dyad-analysis), phylogenetic footprint detection, and genome scanning.

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Introductory Analysis and Validation of CUT&RUN Sequencing Data
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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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  • New matrix-based tools incorporate adaptive background models and Markov-chain estimation for P-value calculation.
  • The software supports random controls using gene selection or random sequence generation with various background models.

    • Main Results:

    • RSAT supports 682 organisms with regularly updated genomes from NCBI and EnsEMBL.
    • The suite offers an intuitive web interface and web services for programmatic integration.
    • RSAT has been utilized by hundreds of researchers globally since 1998, with experimentally validated predictions.

    Conclusions:

    • RSAT is a comprehensive and evolving software suite for cis-regulatory element detection.
    • Its advanced features, including novel matrix-based tools, offer significant advantages over existing software.
    • RSAT's accessibility and proven utility make it a valuable resource for genomic research.