Evidence map›Paper›PMID 32392343›Full record

ArticleNucleic acids research2020

Oviz-Bio: a web-based platform for interactive cancer genomics data visualization.

Wenlong Jia, Hechen Li, Shiying Li, Lingxi Chen, Shuai Cheng Li

Erratum issuedAbstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Wenlong JiaDepartment of Computer Science, City University of Hong Kong, Kowloon Tong 999077, Hong Kong.
Hechen LiDepartment of Computer Science, City University of Hong Kong, Kowloon Tong 999077, Hong Kong.
Shiying LiDepartment of Computer Science, City University of Hong Kong, Kowloon Tong 999077, Hong Kong.
Lingxi ChenDepartment of Computer Science, City University of Hong Kong, Kowloon Tong 999077, Hong Kong.
Shuai Cheng LiDepartment of Computer Science, City University of Hong Kong, Kowloon Tong 999077, Hong Kong.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetics data visualization plays an important role in the sharing of knowledge from cancer genome research. Many types of visualization are widely used, most of which are static and require sufficient coding experience to create. Here, we present Oviz-Bio, a web-based platform that provides interactive and real-time visualizations of cancer genomics data. Researchers can interactively explore visual outputs and export high-quality diagrams. Oviz-Bio supports a diverse range of visualizations on common cancer mutation types, including annotation and signatures of small scale mutations, haplotype view and focal clusters of copy number variations, split-reads alignment and heatmap view of structural variations, transcript junction of fusion genes and genomic hotspot of oncovirus integrations. Furthermore, Oviz-Bio allows landscape view to investigate multi-layered data in samples cohort. All Oviz-Bio visual applications are freely available at https://bio.oviz.org/.

Indexed as

SoftwareComputer GraphicsData VisualizationGene FusionGenetic VariationGenomicsHaplotypesHumansInternetMutationNeoplasmsRetroviridaeVirus Integration

Identifiers

PMID32392343
PMCPMC7319551

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.