DeCovid
DeCovid is a Shiny app designed for exploring basal expression level differences between demographic risk factors, such as age and sex, for COVID-19 Disease Map and COVID-19-related pathway genes expressed in various human tissues. It uses data from the GTEx database to study these differences and helps researchers understand baseline immune patterns towards COVID-19.
Basic Information
| Repository | https://github.com/ConesaLab/DeCovid |
| Documentation | https://github.com/ConesaLab/DeCovid |
| Main publication (DOI) | 10.3390/genes11121447 view |
| Contact email | ana.conesa@csic.es |
| Authors/Maintainers | Ana Conesa |
| Type of application | Desktop application, R/python package |
| Programming languages | RPython |
| Keywords | Omics, Computational Methods, Resources, Transcriptomics, RNA Sequencing (RNA-seq), Data Analysis, Bioinformatics Software and Tools, Analysis packages (R, Python, etc.), Data Visualization, Expression Profiling, Desktop application, Systems Biology, Pathway analysis |
Technical details
| Input file formats | csv, tsv |
| Output file formats | html |
| Software compatibility | Linux, Mac, Windows |
| Hardware requirements | No particular hardware requirements |
| Type of containerization | Docker |
| Wrapper type | None |
| Compatible tools | COVID-19 Disease Map, WikiPathways |
| Funding resource | No funding |
| Funding support | No funding |
Statistics
| Unique users (last 12 months) | <100 |
| Unique users (since first release) | <100 |
| Software downloads (last 12 months) | <100 |
| Software downloads (since first release) | <100 |
| Jobs submitted (last 12 months) | <100 |
| Jobs submitted (since first release) | <100 |
| Repository clones (last 12 months) | <100 |
| Repository clones (since first release) | <100 |
| Citations (last 12 months) | <100 (~2 as of 15/10/2026) |
| Citations (since first release) | <100 (26 as of 15/10/2026) |
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| Technician-supported effort (development) | |
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