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Merge branch 'release-1.2.3'
* release-1.2.3: (27 commits) 🐞 Fix: remove cran-comments.md from build 🐞 Fix: update package date 🐞 Fix: fixed error message 🐞 Fix: dependency list ✨ Feat: move AnnotationDbi to Suggests ✨ Feat: move AnnotationDbi to Suggests ✨ Feat: ignoring `CRAN-SUBMISSION` token ✨ Feat: add cran-comments.md ✨ Feat: add rhub setup 🐞 Fix: typos Increment version number to 1.2.3 🐞 Fix: update package date and language 🐞 Fix: reduce column length 🐞 Fix: syntax Updated NEWS.md 🐞 Fix: replace `seq_len(length())` with `seq_along()` 🐞 Fix: updated CI action version ✨ Feat: relaxed test expectation Increment version number to 1.2.2.9000 ✨ Feat: remove redundant code ...
2 parents f27ce34 + 457e24b commit b2808fa

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-174
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‎.Rbuildignore‎

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binder
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^\.github$
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tests/
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^CRAN-SUBMISSION$
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cran-comments.md

‎.github/workflows/rhub.yaml‎

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# R-hub's generic GitHub Actions workflow file. It's canonical location is at
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# https://github.com/r-hub/actions/blob/v1/workflows/rhub.yaml
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# You can update this file to a newer version using the rhub2 package:
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#
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# rhub::rhub_setup()
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#
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# It is unlikely that you need to modify this file manually.
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name: R-hub
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run-name: "${{ github.event.inputs.id }}: ${{ github.event.inputs.name || format('Manually run by {0}', github.triggering_actor) }}"
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on:
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workflow_dispatch:
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inputs:
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config:
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description: 'A comma separated list of R-hub platforms to use.'
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type: string
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default: 'linux,windows,macos'
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name:
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description: 'Run name. You can leave this empty now.'
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type: string
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id:
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description: 'Unique ID. You can leave this empty now.'
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type: string
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jobs:
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setup:
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runs-on: ubuntu-latest
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outputs:
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containers: ${{ steps.rhub-setup.outputs.containers }}
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platforms: ${{ steps.rhub-setup.outputs.platforms }}
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steps:
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# NO NEED TO CHECKOUT HERE
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- uses: r-hub/actions/setup@v1
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with:
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config: ${{ github.event.inputs.config }}
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id: rhub-setup
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linux-containers:
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needs: setup
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if: ${{ needs.setup.outputs.containers != '[]' }}
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runs-on: ubuntu-latest
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name: ${{ matrix.config.label }}
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strategy:
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fail-fast: false
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matrix:
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config: ${{ fromJson(needs.setup.outputs.containers) }}
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container:
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image: ${{ matrix.config.container }}
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steps:
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- uses: r-hub/actions/checkout@v1
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- uses: r-hub/actions/platform-info@v1
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with:
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token: ${{ secrets.RHUB_TOKEN }}
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job-config: ${{ matrix.config.job-config }}
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- uses: r-hub/actions/setup-deps@v1
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with:
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token: ${{ secrets.RHUB_TOKEN }}
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job-config: ${{ matrix.config.job-config }}
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- uses: r-hub/actions/run-check@v1
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with:
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token: ${{ secrets.RHUB_TOKEN }}
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job-config: ${{ matrix.config.job-config }}
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other-platforms:
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needs: setup
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if: ${{ needs.setup.outputs.platforms != '[]' }}
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runs-on: ${{ matrix.config.os }}
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name: ${{ matrix.config.label }}
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strategy:
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fail-fast: false
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matrix:
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config: ${{ fromJson(needs.setup.outputs.platforms) }}
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steps:
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- uses: r-hub/actions/checkout@v1
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- uses: r-hub/actions/setup-r@v1
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with:
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job-config: ${{ matrix.config.job-config }}
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token: ${{ secrets.RHUB_TOKEN }}
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- uses: r-hub/actions/platform-info@v1
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with:
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token: ${{ secrets.RHUB_TOKEN }}
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job-config: ${{ matrix.config.job-config }}
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- uses: r-hub/actions/setup-deps@v1
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with:
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job-config: ${{ matrix.config.job-config }}
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token: ${{ secrets.RHUB_TOKEN }}
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- uses: r-hub/actions/run-check@v1
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with:
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job-config: ${{ matrix.config.job-config }}
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token: ${{ secrets.RHUB_TOKEN }}

‎.github/workflows/test-coverage.yaml‎

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- name: Upload test results
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if: failure()
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uses: actions/upload-artifact@v3
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uses: actions/upload-artifact@v4
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with:
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name: coverage-test-failures
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path: ${{ runner.temp }}/package

‎.gitignore‎

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inst/doc
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doc
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Meta
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Aux
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Aux
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.Rbuildignore
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CRAN-SUBMISSION

‎DESCRIPTION‎

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Package: DIscBIO
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Date: 2023-11-06
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Date: 2026-01-08
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Title: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics
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Version: 1.2.2
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Version: 1.2.3
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Authors@R:
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c(
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person(
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Imports: methods, TSCAN, httr, mclust, statmod, igraph,
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RWeka, vegan, NetIndices, png, grDevices,
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RColorBrewer, ggplot2, rpart, fpc, cluster, rpart.plot,
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tsne, AnnotationDbi, org.Hs.eg.db, graphics, stats, utils, impute,
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withr
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tsne, graphics, stats, utils, impute, withr
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Depends:
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R (>= 4.0), SingleCellExperiment
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Suggests:
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testthat,
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Seurat
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testthat, Seurat, org.Hs.eg.db, AnnotationDbi
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LazyData: true
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RoxygenNote: 7.2.3
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RoxygenNote: 7.3.3
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URL: https://github.com/ocbe-uio/DIscBIO
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BugReports: https://github.com/ocbe-uio/DIscBIO/issues
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Collate:
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'datasets.R'
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'internal-functions-samr-adapted.R'
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'internal-functions.R'
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'retrieve_geneList.R'
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Language: en-US

‎NAMESPACE‎

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exportMethods(plotSymbolstSNE)
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exportMethods(plottSNE)
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exportMethods(pseudoTimeOrdering)
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import(org.Hs.eg.db)
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importClassesFrom(SingleCellExperiment,SingleCellExperiment)
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importFrom(AnnotationDbi,keys)
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importFrom(NetIndices,GenInd)
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importFrom(RColorBrewer,brewer.pal)
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importFrom(RWeka,J48)
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importFrom(igraph,get.adjacency)
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importFrom(igraph,get.edgelist)
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importFrom(igraph,get.shortest.paths)
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importFrom(igraph,graph.adjacency)
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importFrom(igraph,graph.data.frame)
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importFrom(igraph,graph_from_adjacency_matrix)
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importFrom(igraph,mean_distance)
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importFrom(igraph,minimum.spanning.tree)
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importFrom(igraph,mst)
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importFrom(impute,impute.knn)
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importFrom(mclust,Mclust)
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importFrom(mclust,mclustBIC)
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importFrom(stats,var)
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importFrom(tsne,tsne)
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importFrom(utils,capture.output)
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importFrom(utils,data)
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importFrom(utils,download.file)
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importFrom(utils,read.table)
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importFrom(utils,write.csv)

‎NEWS.md‎

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# DIscBIO 1.2.3
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* Delinted package
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* Removed dependency on `philentropy` and `org.Hs.eg.db` (issue #44, #45)
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# DIscBIO 1.2.2
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* Fixed calculation of Jaccard index (issue #44)

‎R/DIscBIO-classes.R‎

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#' prediction of rare cell types.
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#' @slot cpart A vector containing the final clustering partition computed
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#' by K-means.
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#' @slot fcol A vector contaning the colour scheme for the clusters.
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#' @slot fcol A vector containing the colour scheme for the clusters.
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#' @slot filterpar A list containing the parameters used for cell and gene
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#' filtering based on expression.
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#' @slot clusterpar A list containing the parameters used for the K-means

‎R/DIscBIO-generic-ClustDiffGenes.R‎

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#' @param filename_binom Name of the exported binomial file
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#' @param filename_sigdeg Name of the exported sigDEG file
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#' @importFrom stats pbinom median
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#' @import org.Hs.eg.db
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#' @rdname ClustDiffGenes
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#' @return A list containing two tables.
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#' @export
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DEGsS <- vector()
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DEGsTable <- data.frame()
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for (n in 1:K) {
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if (length(cdiff[[n]][, 1]) == 0) {
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next
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}
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# Generate gene list
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geneList <- retrieve_geneList()
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GL <- c(1, "MTRNR2", "ENSG00000210082")
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GL1 <- c(1, "MTRNR1", "ENSG00000211459")
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geneList <- rbind(geneList, GL, GL1)
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gene_list <- geneList[, 3]
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for (n in 1:K) {
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if (length(cdiff[[n]][, 1]) > 0) {
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p.adj <- p.adjust(cdiff[[n]][, 4], method = "bonferroni")
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out <- cbind(cdiff[[n]], p.adj)
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out <- subset(out, out[, 5] < fdr)
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if (length(out[, 1]) > 0) {
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Regulation <- vector()
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for (i in seq_len(length(out[, 1]))) {
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for (i in seq_along(out[, 1])) {
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if (out[i, 1] > out[i, 2]) {
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Regulation[i] <- "Down"
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} else {
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Regulation[i] <- "Up"
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}
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}
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out <- cbind(out, Regulation)
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if (quiet) {
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suppressMessages(
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geneList <-
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AnnotationDbi::select(
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org.Hs.eg.db,
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keys = keys(org.Hs.eg.db),
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columns = c("SYMBOL", "ENSEMBL")
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)
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)
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GL <- c(1, "MTRNR2", "ENSG00000210082")
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GL1 <- c(1, "MTRNR1", "ENSG00000211459")
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geneList <- rbind(geneList, GL, GL1)
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} else {
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geneList <-
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AnnotationDbi::select(
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org.Hs.eg.db,
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keys = keys(org.Hs.eg.db),
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columns = c("SYMBOL", "ENSEMBL")
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)
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GL <- c(1, "MTRNR2", "ENSG00000210082")
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GL1 <- c(1, "MTRNR1", "ENSG00000211459")
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geneList <- rbind(geneList, GL, GL1)
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}
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genes <- rownames(out)
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gene_list <- geneList[, 3]
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idx_genes <- is.element(gene_list, genes)
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genes2 <- geneList[idx_genes, ]
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Final <- cbind(genes, out)
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}
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}
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}
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if (length(DEGsTable) > 0) {
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colnames(DEGsTable) <- c(
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"Target Cluster", "VS", "Gene number", "File name",

‎R/DIscBIO-generic-Clustexp.R‎

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#' @param object \code{DISCBIO} class object.
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#' @param clustnr Maximum number of clusters for the derivation of the cluster
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#' number by the saturation of mean within-cluster-dispersion. Default is 20.
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#' @param bootnr A numeric value of booststrapping runs for \code{clusterboot}.
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#' @param bootnr A numeric value of bootstrapping runs for \code{clusterboot}.
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#' Default is 50.
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#' @param metric Is the method to transform the input data to a distance object.
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#' Metric has to be one of the following: ["spearman", "pearson", "kendall",

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