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CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts
BACKGROUND: CoMut 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 recur...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624176/ https://www.ncbi.nlm.nih.gov/pubmed/31296206 http://dx.doi.org/10.1186/s12920-019-0510-y |
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author | Huang, Po-Jung Lin, Hou-Hsien Lee, Chi-Ching Chiu, Ling-Ya Wu, Shao-Min Yeh, Yuan-Ming Tang, Petrus Chiu, Cheng-Hsun Lyu, Ping-Chiang Tsai, Pei-Chien |
author_facet | Huang, Po-Jung Lin, Hou-Hsien Lee, Chi-Ching Chiu, Ling-Ya Wu, Shao-Min Yeh, Yuan-Ming Tang, Petrus Chiu, Cheng-Hsun Lyu, Ping-Chiang Tsai, Pei-Chien |
author_sort | Huang, Po-Jung |
collection | PubMed |
description | BACKGROUND: CoMut 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. RESULTS: We 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. CONCLUSIONS: In 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. |
format | Online Article Text |
id | pubmed-6624176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66241762019-07-23 CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts Huang, Po-Jung Lin, Hou-Hsien Lee, Chi-Ching Chiu, Ling-Ya Wu, Shao-Min Yeh, Yuan-Ming Tang, Petrus Chiu, Cheng-Hsun Lyu, Ping-Chiang Tsai, Pei-Chien BMC Med Genomics Research BACKGROUND: CoMut 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. RESULTS: We 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. CONCLUSIONS: In 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. BioMed Central 2019-07-11 /pmc/articles/PMC6624176/ /pubmed/31296206 http://dx.doi.org/10.1186/s12920-019-0510-y Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Huang, Po-Jung Lin, Hou-Hsien Lee, Chi-Ching Chiu, Ling-Ya Wu, Shao-Min Yeh, Yuan-Ming Tang, Petrus Chiu, Cheng-Hsun Lyu, Ping-Chiang Tsai, Pei-Chien CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts |
title | CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts |
title_full | CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts |
title_fullStr | CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts |
title_full_unstemmed | CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts |
title_short | CoMutPlotter: a web tool for visual summary of mutations in cancer cohorts |
title_sort | comutplotter: a web tool for visual summary of mutations in cancer cohorts |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624176/ https://www.ncbi.nlm.nih.gov/pubmed/31296206 http://dx.doi.org/10.1186/s12920-019-0510-y |
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