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CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines
Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While hig...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790544/ https://www.ncbi.nlm.nih.gov/pubmed/33351794 http://dx.doi.org/10.1371/journal.pcbi.1008498 |
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author | Lin, Dongdong Yalamanchili, Hima B. Zhang, Xinmin Lewis, Nathan E. Alves, Christina S. Groot, Joost Arnsdorf, Johnny Bjørn, Sara P. Wulff, Tune Voldborg, Bjørn G. Zhou, Yizhou Zhang, Baohong |
author_facet | Lin, Dongdong Yalamanchili, Hima B. Zhang, Xinmin Lewis, Nathan E. Alves, Christina S. Groot, Joost Arnsdorf, Johnny Bjørn, Sara P. Wulff, Tune Voldborg, Bjørn G. Zhou, Yizhou Zhang, Baohong |
author_sort | Lin, Dongdong |
collection | PubMed |
description | Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research. |
format | Online Article Text |
id | pubmed-7790544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-77905442021-01-27 CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines Lin, Dongdong Yalamanchili, Hima B. Zhang, Xinmin Lewis, Nathan E. Alves, Christina S. Groot, Joost Arnsdorf, Johnny Bjørn, Sara P. Wulff, Tune Voldborg, Bjørn G. Zhou, Yizhou Zhang, Baohong PLoS Comput Biol Research Article Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research. Public Library of Science 2020-12-22 /pmc/articles/PMC7790544/ /pubmed/33351794 http://dx.doi.org/10.1371/journal.pcbi.1008498 Text en © 2020 Lin et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lin, Dongdong Yalamanchili, Hima B. Zhang, Xinmin Lewis, Nathan E. Alves, Christina S. Groot, Joost Arnsdorf, Johnny Bjørn, Sara P. Wulff, Tune Voldborg, Bjørn G. Zhou, Yizhou Zhang, Baohong CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines |
title | CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines |
title_full | CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines |
title_fullStr | CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines |
title_full_unstemmed | CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines |
title_short | CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines |
title_sort | chomics: a web-based tool for multi-omics data analysis and interactive visualization in cho cell lines |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790544/ https://www.ncbi.nlm.nih.gov/pubmed/33351794 http://dx.doi.org/10.1371/journal.pcbi.1008498 |
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