ArticleBMC medical genomics2019
CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts.
Article in BMC medical genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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.
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Who cites it
6 citing papers in PubMed.
- Comut-viz: efficiently creating and browsing comutation plots online.BMC bioinformatics · 2023Article
- A Tale of Two Centers: Visual Exploration of Health Disparities in Cancer Care.IEEE Pacific Visualization Symposium : [proceedings]. IEEE Pacific Visualisation Symposium · 2022Article
- MutScape: an analytical toolkit for probing the mutational landscape in cancer genomics.NAR genomics and bioinformatics · 2021Article
- CoMut: visualizing integrated molecular information with comutation plots.Bioinformatics (Oxford, England) · 2020Article
- Integration of Online Omics-Data Resources for Cancer Research.Frontiers in genetics · 2020Review
- Tumor mutational burden predicts survival in patients with low-grade gliomas expressing mutated IDH1.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoMut plot is widely used in cancer research publications as a visual summary of mutational landscapes in cancer cohorts. This summary plot can inspect gene mutation rate and sample mutation burden with their relevant clinical details, which is a common first step for analyzing the recurrence and co-occurrence of gene mutations across samples. The cBioPortal and iCoMut are two web-based tools that allow users to create intricate visualizations from pre-loaded TCGA and ICGC data. For custom data analysis, only limited command-line packages are available now, making the production of CoMut plots difficult to achieve, especially for researchers without advanced bioinformatics skills. To address the needs for custom data and TCGA/ICGC data comparison, we have created CoMutPlotter, a web-based tool for the production of publication-quality graphs in an easy-of-use and automatic manner.
resultsWe introduce a web-based tool named CoMutPlotter to lower the barriers between complex cancer genomic data and researchers, providing intuitive access to mutational profiles from TCGA/ICGC projects as well as custom cohort studies. A wide variety of file formats are supported by CoMutPlotter to translate cancer mutation profiles into biological insights and clinical applications, which include Mutation Annotation Format (MAF), Tab-separated values (TSV) and Variant Call Format (VCF) files.
conclusionsIn summary, CoMutPlotter is the first tool of its kind that supports VCF file, the most widely used file format, as its input material. CoMutPlotter also provides the most-wanted function for comparing mutation patterns between custom cohort and TCGA/ICGC project. Contributions of COSMIC mutational signatures in individual samples are also included in the summary plot, which is a unique feature of our tool. CoMutPlotter is freely available at http://tardis.cgu.edu.tw/comutplotter .
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Registered trials
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.