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Merge pull request #201 from saeyslab/new-release
NicheNet v2
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.github/workflows/check-bioc.yml

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@@ -20,9 +20,7 @@
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## * GHA: GitHub Action
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## * OS: operating system
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on:
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push:
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pull_request:
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on: workflow_dispatch
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name: R-CMD-check-bioc
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- { os: windows-latest, r: '4.1', bioc: '3.13'}
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env:
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R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
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RSPM_ROOT: https://packagemanager.posit.co.
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RSPM: ${{ matrix.config.rspm }}
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NOT_CRAN: true
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TZ: UTC
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## https://github.com/r-lib/actions/blob/master/examples/check-standard.yaml
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## If they update their steps, we will also need to update ours.
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- name: Checkout Repository
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uses: actions/checkout@v2
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uses: actions/checkout@v3
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## R is already included in the Bioconductor docker images
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- name: Setup R from r-lib
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if: runner.os != 'Linux'
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uses: r-lib/actions/setup-r@master
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uses: r-lib/actions/setup-r@v2
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with:
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r-version: ${{ matrix.config.r }}
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## pandoc is already included in the Bioconductor docker images
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- name: Setup pandoc from r-lib
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if: runner.os != 'Linux'
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uses: r-lib/actions/setup-pandoc@master
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uses: r-lib/actions/setup-pandoc@v2
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- name: Query dependencies
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run: |
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install.packages('remotes')
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saveRDS(remotes::dev_package_deps(dependencies = TRUE), ".github/depends.Rds", version = 2)
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shell: Rscript {0}
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- name: Cache R packages
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- name: Restore R package cache
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if: "!contains(github.event.head_commit.message, '/nocache') && runner.os != 'Linux'"
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uses: actions/cache@v2
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uses: actions/cache@v3
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with:
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path: ${{ env.R_LIBS_USER }}
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key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_12-r-4.0-${{ hashFiles('.github/depends.Rds') }}
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restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_12-r-4.0-
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key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-${{ hashFiles('.github/depends.Rds') }}
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restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-
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- name: Cache R packages on Linux
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if: "!contains(github.event.head_commit.message, '/nocache') && runner.os == 'Linux' "
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uses: actions/cache@v2
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uses: actions/cache@v3
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with:
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path: /home/runner/work/_temp/Library
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key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_12-r-4.0-${{ hashFiles('.github/depends.Rds') }}
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restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_12-r-4.0-
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key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-${{ hashFiles('.github/depends.Rds') }}
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restore-keys: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE_3_17-r-4.3-
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- name: Install Linux system dependencies
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if: runner.os == 'Linux'
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sysreqs=$(Rscript -e 'cat("apt-get update -y && apt-get install -y", paste(gsub("apt-get install -y ", "", remotes::system_requirements("ubuntu", "20.04")), collapse = " "))')
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echo $sysreqs
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sudo -s eval "$sysreqs"
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- name: Install macOS system dependencies
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if: matrix.config.os == 'macOS-latest'
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run: |
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- name: Set BiocVersion
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run: |
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BiocManager::install(version = "${{ matrix.config.bioc }}", ask = FALSE)
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BiocManager::install(version = "${{ matrix.config.bioc }}", ask = FALSE, update = FALSE)
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shell: Rscript {0}
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- name: Install dependencies pass 1
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BiocManager::install("ComplexHeatmap", update = FALSE)
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remotes::install_cran("circlize")
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remotes::install_cran("tidyverse")
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remotes::install_cran("DiagrammeR", type = ifelse("${{ runner.os }}" == "Windows", "win.binary", getOption("pkgType")))
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remotes::install_local(dependencies = TRUE, repos = BiocManager::repositories(), build_vignettes = FALSE, upgrade = TRUE)
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continue-on-error: true
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shell: Rscript {0}

DESCRIPTION

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Package: nichenetr
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Type: Package
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Title: NicheNet: Modeling Intercellular Communication by Linking Ligands to Target Genes
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Version: 1.1.1
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Authors@R: person("Robin", "Browaeys", email = "robin.browaeys@ugent.be",
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role = c("aut", "cre"))
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Version: 2.0.0
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Authors@R: c(person("Robin", "Browaeys", role = c("aut")),
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person("Chananchida", "Sang-aram", role = c("aut", "cre"), email = "chananchida.sangaram@ugent.be"))
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Description: This package allows you the investigate intercellular communication from a computational perspective. More specifically, it allows to investigate how interacting cells influence each other's gene expression. Functionalities of this package (e.g. including predicting extracellular upstream regulators and their affected target genes) build upon a probabilistic model of ligand-target links that was inferred by data-integration.
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License: GPL-3
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Encoding: UTF-8
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LazyData: true
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URL: https://github.com/saeyslab/nichenetr
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BugReports: https://github.com/saeyslab/nichenetr/issues
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RoxygenNote: 7.1.1
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RoxygenNote: 7.1.2
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Depends: R (>= 3.0.0)
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Imports:
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dplyr,
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magrittr,
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circlize,
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ComplexHeatmap,
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grDevices
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Suggests: knitr,
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grDevices,
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ggnewscale,
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ggforce,
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shadowtext
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Suggests:
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knitr,
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rmarkdown,
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testthat,
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doMC,
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mco,
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parallel,
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covr,
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tidyverse

NAMESPACE

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@@ -7,6 +7,7 @@ export(alias_to_symbol_seurat)
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export(apply_hub_corrections)
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export(assess_influence_source)
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export(assess_rf_class_probabilities)
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export(calculate_de)
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export(calculate_fraction_top_predicted)
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export(calculate_fraction_top_predicted_fisher)
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export(calculate_niche_de)
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export(extract_top_fraction_targets)
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export(extract_top_n_ligands)
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export(extract_top_n_targets)
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export(generate_prioritization_tables)
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export(get_active_ligand_receptor_network)
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export(get_active_ligand_target_df)
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export(get_active_ligand_target_matrix)
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export(get_active_regulatory_network)
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export(get_active_signaling_network)
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export(get_expressed_genes)
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export(get_exprs_avg)
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export(get_lfc_celltype)
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export(get_ligand_activities_targets)
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export(get_ligand_signaling_path)
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export(make_ligand_activity_target_exprs_plot)
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export(make_ligand_receptor_lfc_plot)
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export(make_ligand_receptor_lfc_spatial_plot)
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export(make_mushroom_plot)
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export(make_threecolor_heatmap_ggplot)
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export(mlrmbo_optimization)
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export(model_based_ligand_activity_prediction)
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export(process_niche_de)
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export(process_receiver_target_de)
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export(process_spatial_de)
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export(process_table_to_ic)
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export(randomize_complete_network_source_specific)
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export(randomize_datasource_network)
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export(randomize_network)
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export(wrapper_evaluate_single_importances_ligand_prediction)
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import(Seurat)
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import(caret)
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import(cowplot)
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import(dplyr)
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import(e1071)
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import(ggforce)
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import(ggnewscale)
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import(ggplot2)
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import(readr)
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import(shadowtext)
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import(tibble)
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import(tidyr)
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importFrom(ComplexHeatmap,Legend)

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