{ "_id": "6a1adf6e1d7bb097a09ec37c", "Package": "liana", "Type": "Package", "Title": "LIANA: a LIgand-receptor ANalysis frAmework", "Version": "0.1.14.9000", "Authors@R": "c(\nperson(\ngiven = \"Zaoqu\",\nfamily = \"Liu\",\nrole = c(\"cre\", \"ctb\"),\nemail = \"liuzaoqu@163.com\",\ncomment = c(ORCID = \"0000-0002-0452-742X\")\n),\nperson(\ngiven = \"Daniel\",\nfamily = \"Dimitrov\",\nrole = c(\"aut\"),\nemail = \"daniel.dimitrov@uni-heidelberg.de\",\ncomment = c(ORCID = \"0000-0002-5197-2112\")\n),\nperson(\ngiven = \"Charlotte\",\nfamily = \"Boys\",\nrole = c(\"aut\"),\nemail = \"mm228@stud.uni-heidelberg.de\",\ncomment = c(ORCID = \"0000-0003-3955-5110\")\n),\nperson(\ngiven = \"Martin\",\nfamily = \"Garrido Rodriguez\",\nrole = c(\"aut\"),\nemail = \"martin.garrido@uni-heidelberg.de\",\ncomment = c(ORCID = \"0000-0003-4125-5643\")\n),\nperson(\ngiven = \"Denes\",\nfamily = \"Turei\",\nrole = c(\"aut\"),\nemail = \"turei.denes@gmail.com\",\ncomment = c(ORCID = \"0000-0002-7249-9379\")\n),\nperson(\ngiven = \"James\",\nfamily = \"Nagai\",\nrole = c(\"aut\"),\nemail = \"jshinitinaga@ukaachen.de\",\ncomment = c(ORCID = \"0000-0002-7655-7206\")\n))", "Description": "LIANA provides a number of methods and resources for\nligand-receptor interaction inference from scRNA-seq data. This\nversion is specifically designed for Seurat v4 and SeuratObject\nv4 compatibility. It includes improved Python environment\nhandling and better integration with existing workflows.", "License": "GPL-3 + file LICENSE", "URL": "https://zaoqu-liu.github.io/liana/,\nhttps://github.com/Zaoqu-Liu/liana", "BugReports": "https://github.com/Zaoqu-Liu/liana/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "biocViews": "scater, scran, SingleCellExperiment, ComplexHeatmap", "Remotes": [ "sqjin/CellChat", "saezlab/OmnipathR", "saezlab/decoupleR", "Zaoqu-Liu/Connectome" ], "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libcairo2-dev cmake libfontconfig1-dev\nlibfreetype6-dev libfribidi-dev libglpk-dev make\nlibharfbuzz-dev libicu-dev libjpeg-dev libpng-dev libtiff-dev\nlibuv1-dev libwebp-dev libxml2-dev libssl-dev perl python3\nlibx11-dev zlib1g-dev", "Repository": "https://zaoqu-liu.r-universe.dev", "Date/Publication": "2026-01-25 04:59:47 UTC", "RemoteUrl": "https://github.com/Zaoqu-Liu/liana", "RemoteRef": "main", "RemoteSha": 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"_stars": 0, "_contributors": [ { "user": "zaoqu-liu", "count": 9, "uuid": 68080738 } ], "_userbio": { "uuid": 68080738, "type": "user", "name": "LIU Zaoqu", "description": "AI4S" }, "_downloads": { "count": 0, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/liana" }, "_devurl": "https://github.com/zaoqu-liu/liana", "_pkgdown": "https://zaoqu-liu.github.io/liana/", "_searchresults": 231, "_quarto": true, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/liana.html", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_cranurl": false, "_exports": [ "assign_lr_weights", "calculate_gini", "call_cellchat", "call_connectome", "call_italk", "call_natmi", "call_sca", "call_squidpy", "cellchat_formatDB", "chord_freq", "compile_ligrec", "conn_formatDB", "decomplexify", "decompose_tensor", "filter_nonabundant_celltypes", "FormatConnectome", "FormatiTALK", "FormatSCA", "generate_homologs", "generate_lr_geneset", "generate_omni", "generate_orthologs", "get_abundance_summary", "get_c2c_factors", "get_connectome", "get_curated_omni", "get_logfc", "get_lr_resources", "get_natmi", "get_sca", "heat_freq", "italk_formatDB", "join_means", "liana_aggregate", "liana_bysample", "liana_call", "liana_defaults", "liana_dotplot", "liana_heatmap", "liana_pipe", "liana_prep", "liana_tensor_c2c", "liana_wrap", "mean0", "minmax", "plot_abundance_summary", "plot_c2c_cells", "plot_c2c_overview", "plot_context_boxplot", "plot_context_heat", "plot_lr_heatmap", "rank_aggregate", "rank_method", "recomplexify", "sca_formatDB", "select_resource", "show_homologene", "show_methods", "show_resources" ], "_help": [ { "page": "assign_lr_weights", "title": "Helper function to assign weights", "topics": [ "assign_lr_weights" ] }, { "page": "call_cellchat", "title": "Run CellChat with OmniPath function [[DEPRECATED]]", "topics": [ "call_cellchat" ] }, { "page": "call_connectome", "title": "Function to call connectome with databases from OmniPath [[DEPRECATED]]", "topics": [ "call_connectome" ] }, { "page": "call_italk", "title": "Run iTALK with OmniPath data [[DEPRECATED]]", "topics": [ "call_italk" ] }, { "page": "call_natmi", "title": "Call NATMI Pipeline from R with Resources Querried from OmniPath [[DEPRECATED]]", "topics": [ "call_natmi" ] }, { "page": "call_sca", "title": "Function to call SingleCellSignalR with databases from OmniPath [[DEPRECATED]]", "topics": [ "call_sca" ] }, { "page": "call_squidpy", "title": "Call Squidpy Pipeline via reticulate with OmniPath and format results", "topics": [ "call_squidpy" ] }, { "page": "chord_freq", "title": "Frequency ChordDiagram", "topics": [ "chord_freq" ] }, { "page": "decomplexify", "title": "Helper Function to 'decomplexify' ligands and receptors into individual subunits", "topics": [ "decomplexify" ] }, { "page": "decompose_tensor", "title": "Wrapper function to run `cell2cell_tensor` decomposition on a prebuilt tensor.", "topics": [ "decompose_tensor" ] }, { "page": "filter_nonabundant_celltypes", "title": "Filter nun-abundant cell types", "topics": [ "filter_nonabundant_celltypes" ] }, { "page": "FormatConnectome", "title": "Helper function to filter and format connectome", "topics": [ "FormatConnectome" ] }, { "page": "FormatiTALK", "title": "Helper Function to Filter and format iTalk results", "topics": [ "FormatiTALK" ] }, { "page": "FormatNatmi", "title": "Load NATMI results from folder and format appropriately", "topics": [ "FormatNatmi" ] }, { "page": "FormatSCA", "title": "Helper function to format SingleCellSignalR results", "topics": [ "FormatSCA" ] }, { "page": "generate_homologs", "title": "Function to generate a homologous OmniPath resource", "topics": [ "generate_homologs" ] }, { "page": "generate_lr_geneset", "title": "Generate a geneset resource for each LR", "topics": [ "generate_lr_geneset" ] }, { "page": "generate_orthologs", "title": "Deprecated call to generate_homologs", "topics": [ "generate_orthologs" ] }, { "page": "get_c2c_factors", "title": "Returns tensor cell2cell results", "topics": [ "get_c2c_factors" ] }, { "page": "get_connectome", "title": "Function to obtain connectome-like weights", "topics": [ "get_connectome" ] }, { "page": "get_curated_omni", "title": "Function to Generate the Curated (Default) LIANA resource", "topics": [ "get_curated_omni" ] }, { "page": "get_logfc", "title": "Function to obtain logFC weights", "topics": [ "get_logfc" ] }, { "page": "get_lr_resources", "title": "Helper function that returns the name of each intercell resource in OmniPath", "topics": [ "get_lr_resources" ] }, { "page": "get_natmi", "title": "Function to obtain NATMI-like weights", "topics": [ "get_natmi" ] }, { "page": "get_partners", "title": "Retrieves intercellular communication partners (ligands or receptors) from one ligand-receptor resource.", "topics": [ "get_partners" ] }, { "page": "get_permutations", "title": "Helper Function to generate shuffled means", "topics": [ "get_permutations" ] }, { "page": "get_sca", "title": "Function to obtain SingleCellSignalR-like scores", "topics": [ "get_sca" ] }, { "page": "heat_freq", "title": "Communication Frequency heatmap plot", "topics": [ "heat_freq" ] }, { "page": "liana_aggregate", "title": "Function to Aggregate CCC Method Results", "topics": [ "liana_aggregate" ] }, { "page": "liana_bysample", "title": "Wrapper around `liana_wrap` to run liana for each sample.", "topics": [ "liana_bysample" ] }, { "page": "liana_call", "title": "Wrapper Function to obtain scores via liana_pipe", "topics": [ "liana_call" ] }, { "page": "liana_defaults", "title": "Function to pass Default Arguments for each method", "topics": [ "liana_defaults" ] }, { "page": "liana_dotplot", "title": "Liana dotplot interactions by source and target cells", "topics": [ "liana_dotplot" ] }, { "page": "liana_heatmap", "title": "Communication by cell type Heatmap", "topics": [ "liana_heatmap" ] }, { "page": "liana_message", "title": "LIANA message/warning helper function to allow for verbosity", "topics": [ "liana_message" ] }, { "page": "liana_pipe", "title": "Liana Pipe which runs DE analysis and merges needed information for LR inference", "topics": [ "liana_pipe" ] }, { "page": "liana_prep", "title": "Function to handle different types of object as input and do basic quality checks", "topics": [ "liana_prep" ] }, { "page": "liana_scores", "title": "Function to obtain different scoring schemes", "topics": [ "liana_scores" ] }, { "page": "liana_tensor_c2c", "title": "Wrapper function to run `cell2cell_tensor` with LIANA output.", "topics": [ "liana_tensor_c2c" ] }, { "page": "liana_wrap", "title": "LIANA wrapper function", "topics": [ "liana_wrap" ] }, { "page": "min0", "title": "Helper Function which returns the value closest to 0", "topics": [ "min0" ] }, { "page": "minmax", "title": "Helper min-max normalization function", "topics": [ "minmax" ] }, { "page": "plot_c2c_cells", "title": "Plot the product of loadings between the source and target loadings within a factor", "topics": [ "plot_c2c_cells" ] }, { "page": "plot_c2c_overview", "title": "Function to plot an Overview of tensor-c2c results", "topics": [ "plot_c2c_overview" ] }, { "page": "plot_context_boxplot", "title": "Generate boxplots with significance", "topics": [ "plot_context_boxplot" ] }, { "page": "plot_context_heat", "title": "Plot a Heatmap of context loadings", "topics": [ "plot_context_heat" ] }, { "page": "plot_lr_heatmap", "title": "Function to plot a UMAP of context loadings", "topics": [ "plot_lr_heatmap" ] }, { "page": "preprocess_scores", "title": "Helper function to deal with tensor sparsity and liana's scores as in Python", "topics": [ "preprocess_scores" ] }, { "page": "rank_aggregate", "title": "Aggregate CCC Method results and by both magnitude and specificity ranks", "topics": [ "rank_aggregate" ] }, { "page": "rank_method", "title": "Helper function to rank 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