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MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology
With the upgrade and development of the high-throughput sequencing technology, multi-omics data can be obtained at a low cost. However, mapping tools that existed for microbial multi-omics data analysis cannot satisfy the needs of data description and result in high learning costs, complex dependenc...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024144/ https://www.ncbi.nlm.nih.gov/pubmed/35464838 http://dx.doi.org/10.3389/fgene.2022.853612 |
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author | Li, JinHui Sang, Yimeng Zeng, Sen Mo, Shuming Zhang, Zufan He, Sheng Li, Xinying Su, Guijiao Liao, Jianping Jiang, Chengjian |
author_facet | Li, JinHui Sang, Yimeng Zeng, Sen Mo, Shuming Zhang, Zufan He, Sheng Li, Xinying Su, Guijiao Liao, Jianping Jiang, Chengjian |
author_sort | Li, JinHui |
collection | PubMed |
description | With the upgrade and development of the high-throughput sequencing technology, multi-omics data can be obtained at a low cost. However, mapping tools that existed for microbial multi-omics data analysis cannot satisfy the needs of data description and result in high learning costs, complex dependencies, and high fees for researchers in experimental biology fields. Therefore, developing a toolkit for multi-omics data is essential for microbiologists to save effort. In this work, we developed MicrobioSee, a real-time interactive visualization tool based on web technologies, which could visualize microbial multi-omics data. It includes 17 modules surrounding the major omics data of microorganisms such as the transcriptome, metagenome, and proteome. With MicrobioSee, methods for plotting are simplified in multi-omics studies, such as visualization of diversity, ROC, and enrichment pathways for DEGs. Subsequently, three case studies were chosen to represent the functional application of MicrobioSee. Overall, we provided a concise toolkit along with user-friendly, time-saving, cross-platform, and source-opening for researchers, especially microbiologists without coding experience. MicrobioSee is freely available at https://microbiosee.gxu.edu.cn. |
format | Online Article Text |
id | pubmed-9024144 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90241442022-04-23 MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology Li, JinHui Sang, Yimeng Zeng, Sen Mo, Shuming Zhang, Zufan He, Sheng Li, Xinying Su, Guijiao Liao, Jianping Jiang, Chengjian Front Genet Genetics With the upgrade and development of the high-throughput sequencing technology, multi-omics data can be obtained at a low cost. However, mapping tools that existed for microbial multi-omics data analysis cannot satisfy the needs of data description and result in high learning costs, complex dependencies, and high fees for researchers in experimental biology fields. Therefore, developing a toolkit for multi-omics data is essential for microbiologists to save effort. In this work, we developed MicrobioSee, a real-time interactive visualization tool based on web technologies, which could visualize microbial multi-omics data. It includes 17 modules surrounding the major omics data of microorganisms such as the transcriptome, metagenome, and proteome. With MicrobioSee, methods for plotting are simplified in multi-omics studies, such as visualization of diversity, ROC, and enrichment pathways for DEGs. Subsequently, three case studies were chosen to represent the functional application of MicrobioSee. Overall, we provided a concise toolkit along with user-friendly, time-saving, cross-platform, and source-opening for researchers, especially microbiologists without coding experience. MicrobioSee is freely available at https://microbiosee.gxu.edu.cn. Frontiers Media S.A. 2022-04-08 /pmc/articles/PMC9024144/ /pubmed/35464838 http://dx.doi.org/10.3389/fgene.2022.853612 Text en Copyright © 2022 Li, Sang, Zeng, Mo, Zhang, He, Li, Su, Liao and Jiang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Li, JinHui Sang, Yimeng Zeng, Sen Mo, Shuming Zhang, Zufan He, Sheng Li, Xinying Su, Guijiao Liao, Jianping Jiang, Chengjian MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology |
title | MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology |
title_full | MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology |
title_fullStr | MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology |
title_full_unstemmed | MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology |
title_short | MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology |
title_sort | microbiosee: a web-based visualization toolkit for multi-omics of microbiology |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024144/ https://www.ncbi.nlm.nih.gov/pubmed/35464838 http://dx.doi.org/10.3389/fgene.2022.853612 |
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