RSAT 2018: regulatory sequence analysis tools 20th anniversary

Nga Thi Thuy Nguyen, Bruno Contreras-Moreira, Jaime A Castro-Mondragon, Walter Santana-Garcia, Raul Ossio, Carla Daniela Robles-Espinoza, Mathieu Bahin, Samuel Collombet, Pierre Vincens, Denis Thieffry, Jacques van Helden, Alejandra Medina-Rivera (+1 others)
2018 Nucleic Acids Research  
RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATACseq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or
more » ... efactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variationscan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seqbed), to select motifs from motif collections (retrievematrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, vir-tual machines and stand-alone programs at http: // along with the ABims platform in Roscoff, France. We thank Najla Ksouri and Chesco Montardit for providing feedback on the installation of Prunus genomes; Olivier Sand, Matthieu Defrance and Céline Hernandez for regularly answering to RSAT-related questions; Gabriel Moreno-Hagelsieb for helping with the Prokaryote genomes. We thank Mauricio Guzman for designing all logos for RSAT and styling the figures. The testing squad of LIIGH trainees provided tremendous help:
doi:10.1093/nar/gky317 pmid:29722874 pmcid:PMC6030903 fatcat:hau274l2trgfhhtpxtwsqftyna