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-any)DeconvoBuddies_1.5.0.zip(r-4.6-any)DeconvoBuddies_1.5.0.zip(r-4.5-any)
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

7.28 score 11 stars 48 scripts 300 downloads 10 exports 190 dependencies

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

TargetResultTimeFilesSyslog
bioc-checksWARNING295
linux-develWARNING628
source / vignettesOK890
linux-releaseWARNING556
macos-releaseWARNING403
macos-oldrelWARNING373
windows-develWARNING1168
windows-releaseWARNING988
windows-oldrelWARNING859
wasm-releaseOK274

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

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

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

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