Package: ASSIGN 1.43.0
Ying Shen
ASSIGN: Adaptive Signature Selection and InteGratioN (ASSIGN)
ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literature or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature.
Authors:
ASSIGN_1.43.0.tar.gz
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ASSIGN_1.43.0.tgz(r-4.4-any)ASSIGN_1.43.0.tgz(r-4.3-any)
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ASSIGN_1.43.0.tgz(r-4.4-emscripten)ASSIGN_1.43.0.tgz(r-4.3-emscripten)
ASSIGN.pdf |ASSIGN.html✨
ASSIGN/json (API)
NEWS
| # Install 'ASSIGN' in R: |
| install.packages('ASSIGN', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/compbiomed/assign/issues
- excludegenes - Exclude Gene List
- geneList1 - Pathway signature gene sets
- gfrn_geneList - Pathway Signature Gene Lists
- testData1 - Gene expression profiling from cancer patients
- trainingData1 - Gene expression profiling from cell line perturbation experiments
On BioConductor:ASSIGN-1.43.0(bioc 3.21)ASSIGN-1.42.0(bioc 3.20)
softwaregeneexpressionpathwaysbayesian
Last updated 2 months agofrom:e4797e8b66. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 29 2024 |
| R-4.5-win | NOTE | Nov 29 2024 |
| R-4.5-linux | NOTE | Nov 29 2024 |
| R-4.4-win | NOTE | Nov 29 2024 |
| R-4.4-mac | NOTE | Nov 29 2024 |
| R-4.3-win | NOTE | Nov 29 2024 |
| R-4.3-mac | NOTE | Nov 29 2024 |
Exports:assign.convergenceassign.cv.outputassign.mcmcassign.outputassign.preprocessassign.summaryassign.wrapperComBat.step2gather_assign_resultsmerge_dropoptimizeGFRNpcaplotrunassignGFRN
Dependencies:annotateAnnotationDbiaskpassBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64bitopsblobcachemcaToolsclicodetoolscolorspacecpp11crayoncurlDBIedgeRexpmfansifarverfastmapformatRfutile.loggerfutile.optionsgenefiltergenericsGenomeInfoDbGenomeInfoDbDataggplot2gluegplotsgtablegtoolshttrIRangesisobandjsonliteKEGGRESTKernSmoothlabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemsmmunsellmvtnormnlmeopensslpillarpkgconfigplogrpngR6RColorBrewerRlabrlangRSQLiteS4VectorsscalessnowstatmodsurvivalsvasystibbleUCSC.utilsutf8vctrsviridisLitewithrXMLxtableXVectoryamlzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Check the convergence of the MCMC chain | assign.convergence |
| Cross validation output | assign.cv.output |
| The Gibbs sampling algorithm to approximate the joint distribution of the model parameters | assign.mcmc |
| Prediction/validation output for test data | assign.output |
| Input data preprocessing | assign.preprocess |
| Summary of the model parameters estimated by the Gibbs sampling algorithm | assign.summary |
| ASSIGN All-in-one function | assign.wrapper |
| Perform the second step of ComBat | ComBat.step2 |
| Exclude Gene List | excludegenes |
| Gather the ASSIGN results in a specific directory | gather_assign_results |
| Pathway signature gene sets | geneList1 |
| Pathway Signature Gene Lists | gfrn_geneList |
| Combine two data frames | merge_drop |
| Optimize GFRN gene lists lengths | optimizeGFRN |
| Display a PCA Plot of the Data | pcaplot |
| Run optimized single pathway ASSIGN | runassignGFRN |
| Gene expression profiling from cancer patients (test dataset) | testData1 |
| Gene expression profiling from cell line perturbation experiments (training dataset) | trainingData1 |