Evidence map›Paper›PMID 29621972›Full record

ArticleBMC genomics2018

TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets.

Louis T Dang, Markus Tondl, Man Ho H Chiu, Jerico Revote, Benedict Paten, Vincent Tano, Alex Tokolyi, Florence Besse, Greg Quaife-Ryan, Helen Cumming and 11 more

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Louis T DangAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Markus TondlAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Man Ho H ChiuAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Jerico RevoteeResearch, Monash University, Clayton, VIC, Australia.
Benedict PatenUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.
Vincent TanoDepartment of Biochemistry and Molecular Biology, Bio21 Institute and Cell Signalling Research Laboratories, The University of Melbourne, Melbourne, VIC, Australia.
Alex TokolyiAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Florence BesseCNRS, Inserm, Institute of Biology Valrose, Université Côte d'Azur, Parc Valrose, Nice, France.
Greg Quaife-RyanSchool of Biomedical Sciences, The University of Queensland, QLD, Brisbane, Australia.
Helen CummingCentre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Monash University, Clayton, VIC, Australia.
Mark J DrvodelicAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Michael P EichenlaubAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Jeannette C HallabAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Julian S StolperAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Fernando J RosselloAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Marie A BogoyevitchDepartment of Biochemistry and Molecular Biology, Bio21 Institute and Cell Signalling Research Laboratories, The University of Melbourne, Melbourne, VIC, Australia.
David A JansDepartment of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, Australia.
Hieu T NimAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia.
Enzo R PorrelloMurdoch Children's Research Institute, The Royal Children's Hospital, Parkville, VIC, Australia.
James E HudsonSchool of Biomedical Sciences, The University of Queensland, QLD, Brisbane, Australia.
Mirana RamialisonAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash University, Clayton, VIC, Australia. mirana.ramialison@monash.edu.

Funding

Australian Research Council DP1049980National Health and Medical Research Council 1049980
6 · The paper itself

Abstract

backgroundA 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 489:57-74, 2012; Nat 507:462-70, 2014; Nat 507:455-61, 2014; Nat 518:317-30, 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.

resultsWe present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563-5, 2007; Nat Protoc 5:323-34, 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.

conclusionsTrawlerWeb 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 .

Indexed as

SoftwareAnimalsBase SequenceBinding SitesConserved SequenceDNAHigh-Throughput Nucleotide SequencingHumansInternetMesothelinMiceNucleotide MotifsRatsSequence Analysis, DNATranscription FactorsDNAMesothelinMsln protein, ratTranscription FactorsChromatin immunoprecipitationMotif conservationMotif discoveryNext generation sequencingTranscription factor binding site

Identifiers

PMID29621972
PMCPMC5887194

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.