Evidence map›Paper›PMID 28587674›Full record

ArticleBMC bioinformatics2017

NaviSE: superenhancer navigator integrating epigenomics signal algebra.

Alex M Ascensión, Mikel Arrospide-Elgarresta, Ander Izeta, Marcos J Araúzo-Bravo

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 44% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Super-enhancer omics in stem cell.Molecular cancer · 2024
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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

4 authors at 1 institution in 1 country.

Alex M AscensiónComputational Biology and Systems Biomedicine, Biodonostia Health Research Institute, San Sebastián, 20014, Spain.
Mikel Arrospide-ElgarrestaComputational Biology and Systems Biomedicine, Biodonostia Health Research Institute, San Sebastián, 20014, Spain.
Ander IzetaTissue Engineering Laboratory, Bioengineering Area, Biodonostia Health Research Institute, San Sebastián, 20014, Spain. ander.izeta@biodonostia.org.
Marcos J Araúzo-BravoComputational Biology and Systems Biomedicine, Biodonostia Health Research Institute, San Sebastián, 20014, Spain. mararabra@yahoo.co.uk.
Biogipuzkoa Health Research Institute · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSuperenhancers are crucial structural genomic elements determining cell fate, and they are also involved in the determination of several diseases, such as cancer or neurodegeneration. Although there are pipelines which use independent pieces of software to predict the presence of superenhancers from genome-wide chromatin marks or DNA-interaction protein binding sites, there is not yet an integrated software tool that processes automatically algebra combinations of raw data sequencing into a comprehensive final annotated report of predicted superenhancers.

resultsWe have developed NaviSE, a user-friendly streamlined tool which performs a fully-automated parallel processing of genome-wide epigenomics data from sequencing files into a final report, built with a comprehensive set of annotated files that are navigated through a graphic user interface dynamically generated by NaviSE. NaviSE also implements an 'epigenomics signal algebra' that allows the combination of multiple activation and repression epigenomics signals. NaviSE provides an interactive chromosomal landscaping of the locations of superenhancers, which can be navigated to obtain annotated information about superenhancer signal profile, associated genes, gene ontology enrichment analysis, motifs of transcription factor binding sites enriched in superenhancers, graphs of the metrics evaluating the superenhancers quality, protein-protein interaction networks and enriched metabolic pathways among other features. We have parallelised the most time-consuming tasks achieving a reduction up to 30% for a 15 CPUs machine. We have optimized the default parameters of NaviSE to facilitate its use. NaviSE allows different entry levels of data processing, from sra-fastq files to bed files; and unifies the processing of multiple replicates. NaviSE outperforms the more time-consuming processes required in a non-integrated pipeline. Alongside its high performance, NaviSE is able to provide biological insights, predicting cell type specific markers, such as SOX2 and ZIC3 in embryonic stem cells, CDK5R1 and REST in neurons and CD86 and TLR2 in monocytes.

conclusionsNaviSE is a user-friendly streamlined solution for superenhancer analysis, annotation and navigation, requiring only basic computer and next generation sequencing knowledge. NaviSE binaries and documentation are available at: https://sourceforge.net/projects/navise-superenhancer/ .

Indexed as

EpigenomicsUser-Computer InterfaceBiomarkersChromosomesHigh-Throughput Nucleotide SequencingHuman Embryonic Stem CellsHumansInternetMonocytesNeuronsBiomarkersComputational biologyEpigenomicsGraphics user interfaceNext-generation sequencingParallel computingSignal algebraSuperenhancers

Identifiers

PMID28587674
PMCPMC5461685
OpenAlexW2623735819

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.