Package: GeDi 1.3.0

Annekathrin Nedwed

GeDi: Defining and visualizing the distances between different genesets

The package provides different distances measurements to calculate the difference between genesets. Based on these scores the genesets are clustered and visualized as graph. This is all presented in an interactive Shiny application for easy usage.

Authors:Annekathrin Nedwed [aut, cre], Federico Marini [aut]

GeDi_1.3.0.tar.gz
GeDi_1.3.0.zip(r-4.5)GeDi_1.3.0.zip(r-4.4)
GeDi_1.3.0.tgz(r-4.5-any)GeDi_1.3.0.tgz(r-4.4-any)
GeDi_1.3.0.tar.gz(r-4.5-noble)GeDi_1.3.0.tar.gz(r-4.4-noble)
GeDi_1.3.0.tgz(r-4.4-emscripten)
GeDi.pdf |GeDi.html✨
GeDi/json (API)
NEWS

# Install 'GeDi' in R:

install.packages('GeDi', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/annekathrinsilvia/gedi/issues

Datasets:

macrophage_KEGG_example - A sample input RData file
macrophage_Reactome_example - A sample input RData file
macrophage_topGO_example - A sample input RData file
macrophage_topGO_example_small - A small sample input RData file
ppi_macrophage_topGO_example_small - PPI
sample_geneset - A sample input text file
sample_geneset_broken - A broken input text file
sample_geneset_empty - An empty input text file
sample_geneset_small - A small sample input text file
scores_macrophage_topGO_example_small - Sample scores

On BioConductor:GeDi-1.3.0(bioc 3.21)GeDi-1.2.0(bioc 3.20)

gui genesetenrichment software transcription rnaseq visualization clustering pathways reportwriting go kegg reactome shinyapps

5.66 score 1 stars 22 scripts 182 downloads 39 exports 231 dependencies

Last updated 4 months agofrom:81577575b1. Checks:3 OK, 2 NOTE, 1 WARNING. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Jan 28 2025
R-4.5-win	NOTE	Jan 28 2025
R-4.5-mac	WARNING	Jan 28 2025
R-4.5-linux	NOTE	Jan 28 2025
R-4.4-win	OK	Jan 28 2025
R-4.4-mac	OK	Jan 28 2025

Exports:buildClusterGraph buildGraph buildHistogramData calculateJaccard calculateKappa calculateSorensenDice checkInclusion clustering distanceDendro distanceHeatmap enrichmentWordcloud fuzzyClustering GeDi getAdjacencyMatrix getAnnotation getBipartiteGraph getClusterAdjacencyMatrix getGenes getGraphTitle getId getInteractionScore getJaccardMatrix getKappaMatrix getMeetMinMatrix getpMMMatrix getPPI getSorensenDiceMatrix getStringDB goDistance gsHistogram kMeansClustering kNN_clustering louvainClustering markovClustering pamClustering pMMlocal prepareGenesetData scaleGO seedFinding

Dependencies:abind AnnotationDbi ape aplot askpass assorthead backbone base64enc BH BiasedUrn Biobase BiocFileCache BiocGenerics BiocIO BiocNeighbors BiocParallel biomaRt Biostrings bit bit64 bitops blob bs4Dash bslib cachem caTools cellranger chron circlize cli clue cluster clusterProfiler codetools colorspace colourpicker commonmark ComplexHeatmap ComplexUpset cowplot cpp11 crayon crosstalk curl data.table DBI dbplyr DelayedArray dendextend DESeq2 digest doParallel DOSE dplyr DT dynamicTreeCut enrichplot evaluate expm fansi farver fastmap fastmatch fgsea filelock fontawesome foreach formatR fresh fs futile.logger futile.options geneLenDataBase generics GeneTonic GenomeInfoDb GenomeInfoDbData GenomicAlignments GenomicFeatures GenomicRanges GetoptLong ggdendro ggforce ggfun ggnewscale ggplot2 ggplotify ggrepel ggridges ggtangle ggtree GlobalOptions glue GO.db GOSemSim goseq gplots graph gridExtra gridGraphics gson gsubfn gtable gtools hash highr hms htmltools htmlwidgets httpuv httr httr2 igraph IRanges isoband iterators jquerylib jsonlite KEGGREST KernSmooth knitr labeling lambda.r later lattice lazyeval lifecycle locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime miniUI mosdef munsell nlme NLP openssl patchwork pillar pkgconfig plogr plotly plotrix plyr png polyclip prettyunits progress promises proto purrr qvalue R.methodsS3 R.oo R.utils R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RCurl readxl rematch reshape2 restfulr Rhtslib rintrojs rjson rlang rmarkdown Rsamtools RSQLite rstudioapi rtracklayer S4Arrays S4Vectors sass scales scatterpie shape shiny shinyAce shinyBS shinycssloaders shinyjs shinyWidgets slam snow sourcetools SparseArray SparseM sqldf STRINGdb stringi stringr SummarizedExperiment sys systemfonts tibble tidyr tidyselect tidytree tinytex tippy tm topGO treeio tweenr txdbmaker UCSC.utils utf8 vctrs viridis viridisLite visNetwork waiter withr wordcloud2 xfun XML xml2 xtable XVector yaml yulab.utils

The GeDi User's Guide

Annekathrin Silvia Nedwed, Federico Marini

Rendered fromGeDi_manual.Rmdusingknitr::rmarkdownon Jan 28 2025.

Last update: 2024-10-10
Started: 2022-02-09

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Check genesets format	.checkGenesets
Check GeneTonic List format	.checkGTL
Check PPI format	.checkPPI
Check distance scores format	.checkScores
Filter Genesets from the input data	.filterGenesets
Make an educated guess on the separator character	.findSeparator
Map each geneset to the cluster it belongs	.getClusterDatatable
Get gene set descriptions	.getGenesetDescriptions
Determine the number of cores to use for a function	.getNumberCores
Generate a 'data.frame' of graph metrics	.graphMetricsGenesetsDT
Make an educated guess on the separator character	.sepguesser
Build a cluster graph	buildClusterGraph
Construct a graph	buildGraph
Prepare data for 'gsHistogram()'.	buildHistogramData
Calculate the Jaccard distance	calculateJaccard
Calculate the Kappa distance	calculateKappa
Calculate the Sorensen-Dice distance	calculateSorensenDice
Check for subset inclusion	checkInclusion
Cluster genesets.	clustering
Deprecated functions in GeDi	deprecated
Plot a dendrogram	distanceDendro
Plot a heatmap	distanceHeatmap
Visualize the results of an enrichment analysis as word cloud	enrichmentWordcloud
Find cluster from initial seeds	fuzzyClustering
GeDi main function	GeDi
Construct an adjacency matrix	getAdjacencyMatrix
Get the annotation of a STRINGdb object	getAnnotation
Construct a bipartite graph	getBipartiteGraph
Construct an adjacency matrix	getClusterAdjacencyMatrix
Split string of genes	getGenes
Build up the node title	getGraphTitle
Get NCBI ID	getId
Calculate interaction score for two genesets	getInteractionScore
Get Matrix of Jaccard distances	getJaccardMatrix
Get Matrix of Kappa distances	getKappaMatrix
Get Matrix of Meet-Min distances	getMeetMinMatrix
Calculate the pMM distance	getpMMMatrix
Download Protein-Protein Interaction (PPI)	getPPI
Get Matrix of Sorensen-Dice distances	getSorensenDiceMatrix
Get the STRING db entry of a species	getStringDB
Calculate similarity of GO terms	goDistance
Create a histogram plot for gene set sizes	gsHistogram
Calculate clusters based on kMeans clustering	kMeansClustering
Calculate clusters based on kNN clustering	kNN_clustering
Cluster genesets using Louvain clustering.	louvainClustering
A sample input RData file	macrophage_KEGG_example
A sample input RData file	macrophage_Reactome_example
A sample input RData file	macrophage_topGO_example
A small sample input RData file	macrophage_topGO_example_small
Cluster genesets using Markov clustering.	markovClustering
Calculate clusters based on PAM clustering	pamClustering
Calculate local pMM distance	pMMlocal
PPI	ppi_macrophage_topGO_example_small
Split string of genes	prepareGenesetData
A sample input text file	sample_geneset
A broken input text file	sample_geneset_broken
An empty input text file	sample_geneset_empty
A small sample input text file	sample_geneset_small
Scaling (distance) scores	scaleGO
Sample scores	scores_macrophage_topGO_example_small
Find clustering seeds	seedFinding