Package: hipathia 3.7.0
hipathia: HiPathia: High-throughput Pathway Analysis
Hipathia is a method for the computation of signal transduction along signaling pathways from transcriptomic data. The method is based on an iterative algorithm which is able to compute the signal intensity passing through the nodes of a network by taking into account the level of expression of each gene and the intensity of the signal arriving to it. It also provides a new approach to functional analysis allowing to compute the signal arriving to the functions annotated to each pathway.
Authors:
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NEWS
# Install 'hipathia' in R: |
install.packages('hipathia', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- DAdata - Wilcoxon and limma comparison object for nodes, pathways and functional annotations
- brca - BRCA gene expression dataset as SummarizedExperiment
- brca_data - BRCA gene expression dataset
- brca_design - BRCA experimental design
- comp - Wilcoxon comparison of pathways object
- exp_data - Normalized BRCA gene expression dataset
- go_vals - Gene Ontology matrix of the BRCA gene expression dataset
- hidata - Results object
- path_vals - Pathways matrix of the BRCA gene expression dataset
- pathways - Pathways object including pathways has03320 and hsa04012.
- results - Results object
On BioConductor:hipathia-3.7.0(bioc 3.21)hipathia-3.6.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
pathwaysgraphandnetworkgeneexpressiongenesignalinggo
Last updated 23 days agofrom:eda829a650. Checks:ERROR: 2 WARNING: 5. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | FAIL | Nov 18 2024 |
R-4.5-win | WARNING | Nov 18 2024 |
R-4.5-linux | ERROR | Nov 18 2024 |
R-4.4-win | WARNING | Nov 18 2024 |
R-4.4-mac | WARNING | Nov 18 2024 |
R-4.3-win | WARNING | Nov 18 2024 |
R-4.3-mac | WARNING | Nov 18 2024 |
Exports:create_reportDAcompDAoverviewDAreportDAsummaryDAtopdefine_colorsdo_pcado_wilcoxonget_go_namesget_node_namesget_nodes_dataget_path_namesget_paths_dataget_pathways_annotationsget_pathways_listget_pathways_summaryheatmap_plothheadhipathiaload_pathwaysmgi_from_sifmultiple_pca_plotnode_colornode_color_per_denormalize_datanormalize_pathspaths_to_go_ancestorpathway_comparison_plotpca_plotplotVGquantify_termssave_resultstop_pathwaystranslate_datavisualize_report
Dependencies:abindAnnotationDbiAnnotationHubaskpassbackportsbase64encBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocManagerBiocVersionBiostringsbitbit64blobbootbroombslibcachemcarcarDataclicodetoolscoincolorspacecorrplotcowplotcpp11crayoncurlDBIdbplyrDelayedArrayDerivdigestdoBydplyrevaluatefansifarverfastmapfilelockfontawesomeFormulafsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrigraphIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglaterlatticelibcoinlifecyclelimmalme4magrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoiseMetBrewermgcvmicrobenchmarkmimeminqamodelrmodeltoolsmultcompMultiAssayExperimentmunsellmvtnormnlmenloptrnnetnumDerivopensslpbkrtestpillarpkgconfigplogrplyrpngpolynompreprocessCorepromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrmarkdownRSQLiterstatixS4ArraysS4VectorssandwichsassscalesservrSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsysTH.datatibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviridisLitevisNetworkwithrxfunXVectoryamlzlibbioczoo