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TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets.
Dang, Louis T; Tondl, Markus; Chiu, Man Ho H; Revote, Jerico; Paten, Benedict; Tano, Vincent; Tokolyi, Alex; Besse, Florence; Quaife-Ryan, Greg; Cumming, Helen; Drvodelic, Mark J; Eichenlaub, Michael P; Hallab, Jeannette C; Stolper, Julian S; Rossello, Fernando J; Bogoyevitch, Marie A; Jans, David A; Nim, Hieu T; Porrello, Enzo R; Hudson, James E; Ramialison, Mirana.
Afiliação
  • Dang LT; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Tondl M; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Chiu MHH; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Revote J; eResearch, Monash University, Clayton, VIC, Australia.
  • Paten B; UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.
  • Tano V; Department of Biochemistry and Molecular Biology, Bio21 Institute and Cell Signalling Research Laboratories, The University of Melbourne, Melbourne, VIC, Australia.
  • Tokolyi A; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Besse F; CNRS, Inserm, Institute of Biology Valrose, Université Côte d'Azur, Parc Valrose, Nice, France.
  • Quaife-Ryan G; School of Biomedical Sciences, The University of Queensland, QLD, Brisbane, Australia.
  • Cumming H; Centre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Monash University, Clayton, VIC, Australia.
  • Drvodelic MJ; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Eichenlaub MP; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Hallab JC; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Stolper JS; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Rossello FJ; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Bogoyevitch MA; Department of Biochemistry and Molecular Biology, Bio21 Institute and Cell Signalling Research Laboratories, The University of Melbourne, Melbourne, VIC, Australia.
  • Jans DA; Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, Australia.
  • Nim HT; Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
  • Porrello ER; Faculty of Information Technology, Monash University, Clayton, VIC, Australia.
  • Hudson JE; Murdoch Children's Research Institute, The Royal Children's Hospital, Parkville, VIC, Australia.
  • Ramialison M; Department of Physiology, School of Biomedical Sciences, The University of Melbourne, Parkville, VIC, Australia.
BMC Genomics ; 19(1): 238, 2018 Apr 05.
Article em En | MEDLINE | ID: mdl-29621972
ABSTRACT

BACKGROUND:

A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 48957-74, 2012; Nat 507462-70, 2014; Nat 507455-61, 2014; Nat 518317-30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users.

RESULTS:

We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4563-5, 2007; Nat Protoc 5323-34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy.

CONCLUSIONS:

TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at http//trawler.erc.monash.edu.au .
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article