Introduction | What do you get with EMMA? | How does EMMA work? | Installation | Usage example of EMMA: the macrophage dataset | About the data | Getting a list of Differentially Expressed Genes | Performing Functional Enrichment Analysis (FEA) | Entering the EMMA framework | EMMA_run(): Capturing the recorded information | EMMA_show(): Summarizing the recorded information | EMMA_get_record(): Retrieving the recorded information | EMMA_explain(): Summarizing recorded information into text | EMMA with custom/wrapper functions | EMMA_add_custom_metadata(): Adding extra information | EMMA_freeze(): Recording the Analysis Environment | EMMA with iterative workflows | Supported methods and future extensions | Session info | References
Package: EMMA 0.99.4
Najla Abassi
EMMA: EMMA: Enrichment Methods Matter for enabling fully reproducible and provenance-aware pathway analysis
EMMA is a package that provides a provenance-aware execution framework for functional enrichment analyses. It allows users to run enrichment analyses using existing tools and workflows while explicitly capturing analytical parameters during runtime, and returns the native enrichment results output together with structured metadata.
Authors:
EMMA_0.99.4.tar.gz
EMMA_0.99.4.zip(r-4.7)EMMA_0.99.4.zip(r-4.6)EMMA_0.99.4.zip(r-4.5)
EMMA_0.99.4.tgz(r-4.6-any)EMMA_0.99.4.tgz(r-4.5-any)
EMMA_0.99.4.tar.gz(r-4.7-any)EMMA_0.99.4.tar.gz(r-4.6-any)
EMMA_0.99.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
EMMA/json (API)
| # Install 'EMMA' in R: |
| install.packages('EMMA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/imbeimainz/emma/issues
Datasets:
- de_res_IFNg_vs_naive - A sample 'data.frame' containing Differential Expression Analysis, generated with 'DESeq2'
- fea_res - A sample 'list' containing Functional Enrichment Analysis results, generated with 'gprofiler2'
- gene_universe - A sample character vector containing the background gene list used to perform FEA on the 'macrophage' dataset
On BioConductor:EMMA-0.99.4(bioc 3.24)
softwarepathwaysgokegggenesetenrichmentimmunooncologytranscriptomicssinglecellgeneexpressiondifferentialexpressionbioconductorfunctional-enrichment-analysisreproducible-research
Last updated from:7ac847ea2d. Checks:1 NOTE, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 282 | ||
| linux-devel-x86_64 | OK | 446 | ||
| source / vignettes | OK | 475 | ||
| linux-release-x86_64 | OK | 445 | ||
| macos-release-arm64 | OK | 310 | ||
| macos-oldrel-arm64 | OK | 243 | ||
| windows-devel | OK | 470 | ||
| windows-release | OK | 441 | ||
| windows-oldrel | OK | 443 | ||
| wasm-release | OK | 247 |
Exports:EMMA_add_custom_metadataEMMA_explainEMMA_freezeEMMA_get_recordEMMA_runEMMA_show
Dependencies:AnnotationDbiaskpassBiobaseBiocGenericsBiostringsbitbit64blobcachemclicpp11crayoncurlDBIfastmapgenericsgluehttrIRangesjsonliteKEGGRESTlifecyclememoisemimeopensslpkgconfigpngR6rlangRSQLiteS4VectorsSeqinfosysvctrsXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| A sample 'data.frame' containing Differential Expression Analysis, generated with 'DESeq2' | de_res_IFNg_vs_naive |
| EMMA_add_custom_metadata | EMMA_add_custom_metadata |
| EMMA_explain | EMMA_explain |
| EMMA_freeze | EMMA_freeze |
| EMMA_get_record | EMMA_get_record |
| EMMA_run | EMMA_run |
| EMMA_show | EMMA_show |
| EMMA | EMMA-package EMMA EMMA-pkg |
| A sample 'list' containing Functional Enrichment Analysis results, generated with 'gprofiler2' | fea_res |
| A sample character vector containing the background gene list used to perform FEA on the 'macrophage' dataset | gene_universe |
