Package: DeconvoBuddies 1.5.0

Louise Huuki-Myers

DeconvoBuddies: Helper Functions for LIBD Deconvolution

Functions helpful for LIBD deconvolution project. Includes tools for marker finding with mean ratio, expression plotting, and plotting deconvolution results. Working to include DLPFC datasets.

Authors:Louise Huuki-Myers [aut, cre], Leonardo Collado-Torres [ctb], Nicholas J. Eagles [ctb]

DeconvoBuddies_1.5.0.tar.gz
DeconvoBuddies_1.5.0.zip(r-4.7)DeconvoBuddies_1.5.0.zip(r-4.6)DeconvoBuddies_1.5.0.zip(r-4.5)
DeconvoBuddies_1.5.0.tgz(r-4.6-any)DeconvoBuddies_1.5.0.tgz(r-4.5-any)
DeconvoBuddies_1.5.0.tar.gz(r-4.7-any)DeconvoBuddies_1.5.0.tar.gz(r-4.6-any)
DeconvoBuddies_1.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
DeconvoBuddies/json (API)

# Install 'DeconvoBuddies' in R:
install.packages('DeconvoBuddies', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lieberinstitute/deconvobuddies/issues

Datasets:

On BioConductor:DeconvoBuddies-1.5.0(bioc 3.24)DeconvoBuddies-1.4.0(bioc 3.23)

softwaresinglecellrnaseqgeneexpressiontranscriptomicsexperimenthubsoftwarebioconductordeconvolution

7.47 score 10 stars 49 scripts 10 exports 190 dependencies

Last updated from:67f63c74ab. Checks:8 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING288
linux-devel-x86_64WARNING576
source / vignettesOK809
linux-release-x86_64WARNING557
macos-release-arm64WARNING389
macos-oldrel-arm64WARNING389
windows-develWARNING1138
windows-releaseWARNING1140
windows-oldrelWARNING1179
wasm-releaseOK264

Exports:create_cell_colorsfetch_deconvo_datafindMarkers_1vAllget_mean_ratiomake_test_sceplot_composition_barplot_gene_expressplot_marker_expressplot_marker_express_ALLplot_marker_express_List

Dependencies:abindAnnotationDbiAnnotationHubaskpassassortheadattemptbase64encbeachmatbeeswarmbenchmarkmebenchmarkmeDataBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIOBiocManagerBiocNeighborsBiocParallelBiocSingularBiocVersionBiostringsbitbit64bitopsblobblusterbslibcachemcigarillocirclizecliclueclustercodetoolscolorspacecommonmarkComplexHeatmapconfigcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdigestdoParalleldplyrdqrngDTedgeRevaluateExperimentHubfarverfastmapfilelockFNNfontawesomeforeachformatRfsfutile.loggerfutile.optionsgenericsGenomicAlignmentsGenomicRangesGetoptLongggbeeswarmggplot2ggrepelGlobalOptionsgluegolemgridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrhttr2igraphIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalocfitmagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisemetapodmimeopensslotelpaletteerpheatmappillarpkgconfigplotlyplyrpngprismaticpromisespurrrR6rafalibrappdirsRColorBrewerRcppRcppAnnoyRcppEigenRcppMLRcppProgressRCurlrematch2reshape2restfulrRhtslibrjsonrlangrmarkdownRsamtoolsRSpectraRSQLiterstudioapirsvdrtracklayerRtsneS4ArraysS4VectorsS7sassScaledMatrixscalesscaterscranscuttleSeqinfosessioninfoshapeshinyshinyWidgetsSingleCellExperimentsitmosnowsourcetoolsSparseArraysparseMatrixStatsSpatialExperimentspatialLIBDstatmodstringistringrSummarizedExperimentsystibbletidyrtidyselecttinytexutf8uwotvctrsviporviridisviridisLitewithrxfunXMLxtableXVectoryaml

Finding Marker Genes with DeconvoBuddies
Introduction | What are Marker Genes? | How can we select marker genes? | The Mean Ratio Method | Goals of this Vignette | 1. Install and load required packages | Install DeconvoBuddies | Load Other Packages | 2. Download DLPFC snRNA-seq data. | 3. Find MeanRatio marker genes | 4. Find 1vALL marker genes | Run 1vALL DE to find markers for each cell type - takes 5min+ | marker_stats_1vAll <- findMarkers_1vAll( | sce = sce, # sce is the SingleCellExperiment with our data | assay_name = "counts", | cellType_col = "cellType_broad_hc", # column in colData with cell type info | mod = "~BrNum" # Control for donor stored in "BrNum" with mod | raw_logFC = TRUE # also retain raw logFC in addition to standardized | ) | load 1vAll data to save time, data is equivalent to the above code | 5. Compare Marker Gene Selection | Hockey Stick Plots | 6. Visualize Marker Genes Expression | Summary | Reproducibility | Bibliography
Rendered fromMarker_Finding.Rmdusingknitr::rmarkdown

Last update: 2026-03-03
Started: 2024-08-05

Deconvolution Benchmark in Human DLPFC
Introduction | What is Deconvolution? | Deconvolution Methods | Goals of this Vignette | Video Tutorial | Basics | 1. Install and load required packages | Install DeconvoBuddies | Load Other Packages | 2. Download DLPFC RNA-seq data, and reference snRNA-seq data. | Bulk RNA-seq data | Reference snRNA-seq data | Orthogonal Cell Type Proportion from RNAScope/IF | 3. Select Marker Genes | Use get_mean_ratio() to find marker genes. | Plot the top marker genes | Create a List of Marker Genes | 4. Prep Data and Run Bisque | Prepare data | Run Bisque | Explore Output | 5. Explore deconvolution output and create composition plots with DeconvoBuddies tools | 6. Check proportion against RNAScope/IF estimated proportions | 7. How to run deconvolution with hspe | Conclusion | Reproducibility | Bibliography
Rendered fromDeconvolution_Benchmark_DLPFC.Rmdusingknitr::rmarkdown

Last update: 2025-07-28
Started: 2024-03-27

Get Started with DeconvoBuddies
Introduction | Basics | Install DeconvoBuddies | Required knowledge | Asking for help | Citing DeconvoBuddies | Quick start to using DeconvoBuddies | Access Data | Access and snRNA-seq example data | Explore snRNA-seq data in sce_DLPFC_example | Access Bulk RNA-seq data | Explore bulk data in rse_gene | Plotting Tools | Creating A Cell Type Color palette | Preview "classic" colors | Preview "gg" colors | Preview "tableau" colors | Check the color hex codes for "tableau" | Provide a palette from RColorBrewer | Plot Expression of Top Markers | plot expression of the top 6 Astro marker genes | Reproducibility | Bibliography
Rendered fromDeconvoBuddies.Rmdusingknitr::rmarkdown

Last update: 2025-07-25
Started: 2021-11-30