EJPRD WP13 case-studies workflows from phase 1.
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SEEK ID: https://workflowhub.eu/projects/40
Public web page: https://www.ejprarediseases.org/
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Team created: 23rd Jun 2021
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Teams: EJPRD WP13 case-studies workflows
Organizations: EJP-RD
https://orcid.org/0000-0002-0637-9950Teams: EJPRD WP13 case-studies workflows
Organizations: EJP-RD
https://orcid.org/0000-0002-0613-3651Teams: EJPRD WP13 case-studies workflows
Organizations: Maastricht University
https://orcid.org/0000-0002-7770-620XTeams: LBI-RUD, EJPRD WP13 case-studies workflows
Organizations: LBI-RUD, EJP-RD
https://orcid.org/0000-0002-0320-0214Teams: EJPRD WP13 case-studies workflows
Organizations: Maastricht University
https://orcid.org/0000-0003-2878-4049Teams: EJPRD WP13 case-studies workflows
Organizations: EJP-RD
https://orcid.org/0000-0002-8972-9206Teams: EJPRD WP13 case-studies workflows
Organizations: EJP-RD
https://orcid.org/0000-0001-5980-8002Teams: GalaxyProject SARS-CoV-2, nf-core viralrecon, EOSC-Life - Demonstrator 7: Rare Diseases, iPC: individualizedPaediatricCure, EJPRD WP13 case-studies workflows, TransBioNet, OpenEBench, ELIXIR Proteomics
Organizations: Barcelona Supercomputing Center (BSC-CNS), ELIXIR
https://orcid.org/0000-0003-4929-1219Expertise: Bioinformatics, Computer Science, AI, Machine Learning
Computer Engineer in Barcelona Supercomputing Center (BSC)
Teams: EJPRD WP13 case-studies workflows
Organizations: EJP-RD
https://orcid.org/0000-0002-2319-2960Teams: EJPRD WP13 case-studies workflows
Organizations: EJP-RD
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This workflow is part of the EJP RD case study on CAKUT published here: Bayjanov, J.R., Doornbos, C., Ozisik, O. et al. Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT. Sci Rep 14, 20731 (2024). https://doi.org/10.1038/s41598-024-71721-8
Creator: Juma Bayjan
Submitter: Juma Bayjan
Workflow for gene set enrichment analsysis (GSEA) and co-expression analysis (WGCNA) on transcriptomics data to analyze pathways affected in Porto-Sinusoidal Vascular Disease.
Type: Common Workflow Language
Creators: Aishwarya Iyer, Friederike Ehrhart
Submitter: Aishwarya Iyer
Workflow for Creating a large disease network from various datasets and databases for IBM, and applying the active subnetwork identification method MOGAMUN.
Type: Common Workflow Language
Creators: Daphne Wijnbergen, Mridul Johari
Submitter: Daphne Wijnbergen
Joint multi-omics dimensionality reduction approaches for CAKUT data using peptidome and proteome data
Brief description In (Cantini et al. 2020), Cantini et al. evaluated 9 representative joint dimensionality reduction (jDR) methods for multi-omics integration and analysis and . The methods are Regularized Generalized Canonical Correlation Analysis (RGCCA), Multiple co-inertia analysis (MCIA), Multi-Omics Factor Analysis (MOFA), Multi-Study Factor Analysis (MSFA), iCluster, Integrative NMF ...
Type: Snakemake
Creators: Ozan Ozisik, Juma Bayjan, Cenna Doornbos, Friederike Ehrhart, Matthias Haimel, Laura Rodriguez-Navas, José Mª Fernández, Eleni Mina, Daniël Wijnbergen
Submitter: Juma Bayjan
For integrative analysis of CAKUT multi-omics data DIABLO method of the mixOmics package (version 6.10.9. Singh et. al. 2019) was used with sPLS-DA (sparse Partial Least Squares Discriminant Analysis Discriminant Analysis) and PLS-DA classification.
Type: Snakemake
Creators: Juma Bayjan, Ozan Ozisik, Cenna Doornbos, Friederike Ehrhart
Submitter: Juma Bayjan
In this analysis, we created an extended pathway, using the WikiPathways repository (Version 20210110) and the three -omics datasets. For this, each of the three -omics datasets was first analyzed to identify differentially expressed elements, and pathways associated with the significant miRNA-protein links were detected. A miRNA-protein link is deemed significant, and may possibly be implying causality, if both a miRNA and its target are significantly differentially expressed.
The peptidome and ...
Type: Snakemake
Creators: Woosub Shin, Friederike Ehrhart, Juma Bayjan, Cenna Doornbos, Ozan Ozisik
Submitter: Juma Bayjan