2019
Huang, P. -J.; Lin, H. -H.; Lee, C. -C.; Chiu, L. -Y.; Wu, S. -M.; Yeh, Y. -M.; Tang, P.; Chiu, C. -H.; Lyu, P. -C.; Tsai, P. -C.
CoMutPlotter: A web tool for visual summary of mutations in cancer cohorts Journal Article
In: BMC Medical Genomics, 12 , 2019, ISSN: 17558794, (cited By 2).
Abstract | Links | BibTeX | 標籤: Cohort Studies; Computational Biology; Computer Graphics; Humans; Internet; Mutation; Neoplasms
@article{Huang2019,
title = {CoMutPlotter: A web tool for visual summary of mutations in cancer cohorts},
author = {P. -J. Huang and H. -H. Lin and C. -C. Lee and L. -Y. Chiu and S. -M. Wu and Y. -M. Yeh and P. Tang and C. -H. Chiu and P. -C. Lyu and P. -C. Tsai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069492276&doi=10.1186%2fs12920-019-0510-y&partnerID=40&md5=67d7a1a9297413695b8d1b5cf820c44b},
doi = {10.1186/s12920-019-0510-y},
issn = {17558794},
year = {2019},
date = {2019-01-01},
journal = {BMC Medical Genomics},
volume = {12},
publisher = {BioMed Central Ltd.},
abstract = {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. © 2019 The Author(s).},
note = {cited By 2},
keywords = {Cohort Studies; Computational Biology; Computer Graphics; Humans; Internet; Mutation; Neoplasms},
pubstate = {published},
tppubtype = {article}
}
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. © 2019 The Author(s).