Evidence map›Paper›PMID 29259323›Full record

ArticleScientific reports2017

INTEGRATE-Vis: a tool for comprehensive gene fusion visualization.

Jin Zhang, Teng Gao, Christopher A Maher

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. TargetedCell reports methods · 2023
    Article
  4. Article
  5. Article
  6. Article
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

3 authors.

Jin ZhangDepartment of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, 63110, USA.
Teng GaoMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, 63110, USA.
Christopher A MaherMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, 63110, USA. christophermaher@wustl.edu.

Funding

Characterization of Cancer Transcriptomes using Next Generation SequencingR00CA149182 · NCI · WASHINGTON UNIVERSITY · PI MAHER, CHRISTOPHER A · 2011 to 2013
$685k
CLONAL EVOLUTION OF STRUCTURAL VARIANTS IN THE PROGRESSION OF METASTATIC COLORECTR21CA185983 · NCI · WASHINGTON UNIVERSITY · PI MAHER, CHRISTOPHER A · 2014 to 2015
$315k
NCI NIH HHS R00 CA149182NCI NIH HHS R21 CA185983
6 · The paper itself

Abstract

Despite the increasing quantity of tools for accurately predicting gene fusion candidates from sequencing data, we are still faced with the critical challenge of visualizing the corresponding gene fusion products to infer their biological consequence (i.e. novel protein and increased gene expression). This is currently accomplished by manually inspecting and inferring the biological consequence of top scoring gene fusion candidates. This labor-intensive process could be made easier by automating the annotation of gene fusion products and generating easily interpretable visualizations. We developed a gene fusion visualization tool, called INTEGRATE-Vis, that generates comprehensive, highly customizable, publication-quality graphics focused on annotating each gene fusion at the transcript- and protein-level and assessing expression within an individual sample or across a patient cohort. INTEGRATE-Vis is the first comprehensive gene fusion visualization tool to help a user infer the potential consequence of a gene fusion event. It has potential utility in both research and clinical settings. INTEGRATE-Vis is available at https://github.com/ChrisMaherLab/INTEGRATE-Vis .

Indexed as

ComputersGene FusionGenomicsHigh-Throughput Nucleotide SequencingHumansSoftware

Identifiers

PMID29259323
PMCPMC5736641

What OpenQuestion holds

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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.