Computational workflow for functional characterization of COVID-19 through secondary data analysis
Summary: Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes. We present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | STAR Protocols |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666166721005797 |
| _version_ | 1831758575445213184 |
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| author | Sudhir Ghandikota Mihika Sharma Anil G. Jegga |
| author_facet | Sudhir Ghandikota Mihika Sharma Anil G. Jegga |
| author_sort | Sudhir Ghandikota |
| collection | DOAJ |
| description | Summary: Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes. We present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein interactions, single-cell RNA-seq markers, and phenotype-genotype associations to identify functional feature complexes. These feature modules represent a higher order multifeatured machines collectively working toward common pathophysiological goals. We apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases.For complete details on the use and execution of this protocol, please refer to Ghandikota et al. (2021). |
| first_indexed | 2024-12-22T00:51:07Z |
| format | Article |
| id | doaj.art-90b2d06ad9e3475bb471937ead5c80dc |
| institution | Directory Open Access Journal |
| issn | 2666-1667 |
| language | English |
| last_indexed | 2024-12-22T00:51:07Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | STAR Protocols |
| spelling | doaj.art-90b2d06ad9e3475bb471937ead5c80dc2022-12-21T18:44:26ZengElsevierSTAR Protocols2666-16672021-12-0124100873Computational workflow for functional characterization of COVID-19 through secondary data analysisSudhir Ghandikota0Mihika Sharma1Anil G. Jegga2Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA; Department of Computer Science, University of Cincinnati College of Engineering, Cincinnati, OH, USA; Corresponding authorDivision of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USADivision of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA; Department of Computer Science, University of Cincinnati College of Engineering, Cincinnati, OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Corresponding authorSummary: Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes. We present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein interactions, single-cell RNA-seq markers, and phenotype-genotype associations to identify functional feature complexes. These feature modules represent a higher order multifeatured machines collectively working toward common pathophysiological goals. We apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases.For complete details on the use and execution of this protocol, please refer to Ghandikota et al. (2021).http://www.sciencedirect.com/science/article/pii/S2666166721005797BioinformaticsSingle CellHealth SciencesGenomicsRNAseqImmunology |
| spellingShingle | Sudhir Ghandikota Mihika Sharma Anil G. Jegga Computational workflow for functional characterization of COVID-19 through secondary data analysis STAR Protocols Bioinformatics Single Cell Health Sciences Genomics RNAseq Immunology |
| title | Computational workflow for functional characterization of COVID-19 through secondary data analysis |
| title_full | Computational workflow for functional characterization of COVID-19 through secondary data analysis |
| title_fullStr | Computational workflow for functional characterization of COVID-19 through secondary data analysis |
| title_full_unstemmed | Computational workflow for functional characterization of COVID-19 through secondary data analysis |
| title_short | Computational workflow for functional characterization of COVID-19 through secondary data analysis |
| title_sort | computational workflow for functional characterization of covid 19 through secondary data analysis |
| topic | Bioinformatics Single Cell Health Sciences Genomics RNAseq Immunology |
| url | http://www.sciencedirect.com/science/article/pii/S2666166721005797 |
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