Automated transcriptomics data analysis workflow using pathway and network analysis approaches
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In this study, we developed an automated and reproducible workflow for transcriptomics data analysis using network biology approaches. The analyses are fully automated in R with clusterProfiler and RCy3 to connect to the widely adopted network analysis software Cytoscape including the CyTargetLinker app for network extension. For demonstration, we use a publicly available dataset from Blanco-Melo et al., GSE147507 obtained from GEO. After pre-processing with DESeq2, the dataset contains log2 fold changes, p-values, and adjusted p-values of 21,797 genes from the human lung epithelial cell line NHBE comparing expression levels before and after SARS-CoV-2 infection. The script is available on Github repository. URL: https://github.com/BiGCAT-UM/COVID19-ZonMw/tree/main/Analysis_NHBE_COVID19
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Creators and SubmitterCreators
Nhung Pham
Martina Kutmon
Friederike Ehrhart
Finterly Hu
Egon Willighagen- Chris Evelo
Alexander Pico
Submitter
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Created: 9th Apr 2021 at 08:54
Last updated: 12th Apr 2021 at 07:34
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Projects: COVID-19 Disease Map
Institutions: University Maastricht
https://orcid.org/0000-0002-7770-620X
Projects: COVID-19 Disease Map
Institutions: University Maastricht
https://orcid.org/0000-0002-8416-4533
Projects: COVID-19 Disease Map
Institutions: University Maastricht
https://orcid.org/0000-0002-7699-8191
My research interest is in studying cellular and molecular pathways of COVID-19 disease.
Projects: COVID-19 Disease Map
Institutions: Gladstone Institutes
https://orcid.org/0000-0001-5706-2163
Bioinformatics core director at Gladstone Institutes. Executive director of the National Resource for Network Biology. Co-founder of WikiPathways. Co-developer of Cytoscape.
Projects: COVID-19 Disease Map, VHP project
Institutions: University Maastricht
The Disease Maps Project is designed as a large-scale community effort. It is a network of groups that work together in order to better understand disease mechanisms. The project exchanges best practices, share information, develop tools to make it easier for all the involved groups to achieve their goals.
Projects: COVID-19 Disease Map
Web page: https://disease-maps.org
Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.
Programme: Disease Maps
Public web page: http://doi.org/10.17881/covid19-disease-map
In this investigation we aim to develop automatic workflows to analyze COVID19 Omics data to understand and predict the molecular pathways depicting host-virus interaction.
