Evidence map›Paper›PMID 37264324›Full record

ArticleBMC bioinformatics2023

Comut-viz: efficiently creating and browsing comutation plots online.

Qiaonan Duan, Weiyi Wang, Feiling Feng, Xiaoqing Jiang, Hao Chen, Dadong Zhang, Tongyi Zhang

Abstract read
In one paragraph

Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Qiaonan Duan *Department of Translational Medicine, 3D Medicines Inc., Shanghai, China.
Weiyi Wang *General Surgery Department, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
Feiling Feng *Department of Biliary Tract Surgery I, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, China.
Xiaoqing JiangDepartment of Biliary Tract Surgery I, Third Affiliated Hospital of Naval Medical University (Eastern Hepatobiliary Surgery Hospital), Shanghai, China.
Hao ChenDepartment of Translational Medicine, 3D Medicines Inc., Shanghai, China.
Dadong ZhangDepartment of Translational Medicine, 3D Medicines Inc., Shanghai, China. dadong.zhang@3dmedcare.com.
Tongyi ZhangGeneral Surgery Department, Huadong Hospital Affiliated to Fudan University, Shanghai, China. tongyizhang1983@163.com.

Funding

Second Military Medical University 2017JZ11Shanghai Jiading District Health Commission 2020-ZD-01
6 · The paper itself

Abstract

backgroundComutation plot is a widely used visualization method to deliver a global view of the mutation landscape of large-scale genomic studies. Current tools for creating comutation plot are either offline packages that require coding or online web servers with varied features. When a package is used, it often requires repetitive runs of code to adjust a single feature that might only be a few clicks in a web app. But web apps mostly have limited capacity for customization and cannot handle very large genomic files.

resultsTo improve on existing tools, we identified features that are most frequently adjusted in creating a plot and incorporate them in Comut-viz that interactively filters and visualizes mutation data as downloadable plots. It includes colored labels for numeric metadata, a preloaded palette for changing colors and two input boxes for adjusting width and height. It accepts standard mutation annotation format (MAF) files as input and can handle large MAF files with more than 200 k rows. As a front-end only app, Comut-viz guarantees privacy of user data and no latency in the analysis.

conclusionsComut-viz is a highly responsive and extensible web app to make comutation plots. It provides customization for frequently adjusted features and accepts large genomic files as input. It is suitable for genomic studies with more than a thousand samples.

Indexed as

GenomeGenomicsMutationSoftwareComutation plotGenomic analysisMutationVisualizationWeb server

Identifiers

PMID37264324
PMCPMC10236844

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.