Package: scMappR 1.0.11

scMappR: Single Cell Mapper

The single cell mapper (scMappR) R package contains a suite of bioinformatic tools that provide experimentally relevant cell-type specific information to a list of differentially expressed genes (DEG). The function "scMappR_and_pathway_analysis" reranks DEGs to generate cell-type specificity scores called cell-weighted fold-changes. Users input a list of DEGs, normalized counts, and a signature matrix into this function. scMappR then re-weights bulk DEGs by cell-type specific expression from the signature matrix, cell-type proportions from RNA-seq deconvolution and the ratio of cell-type proportions between the two conditions to account for changes in cell-type proportion. With cwFold-changes calculated, scMappR uses two approaches to utilize cwFold-changes to complete cell-type specific pathway analysis. The "process_dgTMatrix_lists" function in the scMappR package contains an automated scRNA-seq processing pipeline where users input scRNA-seq count data, which is made compatible for scMappR and other R packages that analyze scRNA-seq data. We further used this to store hundreds up regularly updating signature matrices. The functions "tissue_by_celltype_enrichment", "tissue_scMappR_internal", and "tissue_scMappR_custom" combine these consistently processed scRNAseq count data with gene-set enrichment tools to allow for cell-type marker enrichment of a generic gene list (e.g. GWAS hits). Reference: Sokolowski,D.J., Faykoo-Martinez,M., Erdman,L., Hou,H., Chan,C., Zhu,H., Holmes,M.M., Goldenberg,A. and Wilson,M.D. (2021) Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes. NAR Genomics and Bioinformatics. 3(1). Iqab011. <doi:10.1093/nargab/lqab011>.

Authors:Dustin Sokolowski [aut, cre], Mariela Faykoo-Martinez [aut], Lauren Erdman [aut], Houyun Hou [aut], Cadia Chan [aut], Helen Zhu [aut], Melissa Holmes [aut], Anna Goldenberg [aut], Michael Wilson [aut]

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

Peer review:

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On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

29 exports 4 stars 0.91 score 229 dependencies 1 mentions 9 scripts 364 downloads

Last updated 1 years agofrom:43e80e2977. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 02 2024
R-4.5-winOKSep 02 2024
R-4.5-linuxOKSep 02 2024
R-4.4-winOKSep 02 2024
R-4.4-macOKSep 02 2024
R-4.3-winOKSep 02 2024
R-4.3-macOKSep 02 2024

Exports:cellmarker_enrichcoEnrichcompare_deconvolution_methodscwFoldChange_evaluateDeconRNAseq_CRANdeconvolute_and_contextualizeextract_genes_cellgeneres_to_heatmapget_gene_symbolget_signature_matricesgProfiler_cellWeighted_Foldchangegsva_cellIdentifyheatmap_generationhuman_mouse_ct_marker_enrichmake_TF_barplotpathway_enrich_internalplotBPprocess_dgTMatrix_listsprocess_from_countscMappR_and_pathway_analysisseurat_to_generessingle_gene_preferencestissue_by_celltype_enrichmenttissue_scMappR_customtissue_scMappR_internaltochrtoNumtopgenes_extracttwo_method_pathway_enrichment

Dependencies:abindADAPTSannotateAnnotationDbiaskpassbase64encbeachmatBHBiobaseBiocFileCacheBiocGenericsBiocParallelBiocSingularBiostringsbitbit64bitopsblobbslibcachemcaToolsclasscliclustercodetoolscolorspaceComICScommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdeldirdigestdoParalleldoRNGdotCall64downloaderdplyrdqrnge1071evaluatefansifarverfastDummiesfastmapfilelockfitdistrplusFNNfontawesomeforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglmnetglobalsgluegoftestgplotsgProfileRgprofiler2graphgridExtraGSEABaseGSVAgtablegtoolsHDF5ArrayherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobanditeratorsitertoolsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlifecyclelimSolvelistenvlmtestlpSolvemagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImissForestmunsellnlmennlsopensslparallellypatchworkpbapplypcaMethodspheatmappillarpkgconfigplogrplotlyplyrpngpolyclippreprocessCoreprogressrpromisesproxypurrrquadprogquantmodR6randomForestrangerRANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLRCurlreshapereshape2reticulaterhdf5rhdf5filtersRhdf5librjsonrlangrmarkdownrngtoolsROCRrprojrootRSpectraRSQLitersvdRtsneS4ArraysS4VectorssassScaledMatrixscalesscattermoresctransformSeuratSeuratObjectshapeshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArraysparseMatrixStatsSpatialExperimentspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexTTRUCSC.utilsutf8uwotvctrsviridisLitewithrxfunXMLxtablextsXVectoryamlzlibbioczoo

single cell Mapper (scMappR)

Dustin Sokolowski

Rendered fromscMappR_Vignette.Rmdusingknitr::rmarkdownon Sep 02 2024.

Last update: 2022-03-07
Started: 2020-03-04

Readme and manuals

Help Manual

Help pageTopics
Fisher's Exact Cell-Type Identification.cellmarker_enrich
Identify co-expressed cell-typescoEnrich
compare_deconvolution_methodscompare_deconvolution_methods
Measure cell-type specificity of cell-weighted Fold-changescwFoldChange_evaluate
DeconRNASeq CRAN compatibleDeconRNAseq_CRAN
Generate cell weighted Fold-Changes (cwFold-changes)deconvolute_and_contextualize
Extract Markersextract_genes_cell
Generate signature matrixgeneres_to_heatmap
Internal - get gene symbol from Panglao.db assigned gene-names (symbol-ensembl).get_gene_symbol
Get signature matrices.get_signature_matrices
gmt_examplegmt
Pathway enrichment for cwFold-changesgProfiler_cellWeighted_Foldchange
Cell-type naming with GSVAgsva_cellIdentify
Generate Heatmapheatmap_generation
Consensus cell-type naming (Fisher's Exact)human_mouse_ct_marker_enrich
Plot g:profileR Barplot (TF)make_TF_barplot
Internal - Pathway enrichment for cellWeighted_Foldchanges and bulk gene listpathway_enrich_internal
PBMC_scMappRPBMC_example
Plot gProfileR BarplotplotBP
Preoptic_AreaPOA_example
Count Matrix To Signature Matrixprocess_dgTMatrix_lists
Count Matrix To Seurat Objectprocess_from_count
Generate cellWeighted_Foldchanges, visualize, and enrich.scMappR_and_pathway_analysis
scMappR_tissuesscMappR_tissues
Identify all cell-type markersseurat_to_generes
Single cell-type gene preferencessingle_gene_preferences
single_cell_processsm
tissue_by_celltype_enrichmenttissue_by_celltype_enrichment
Gene List Visualization and Enrichment with Custom Signature Matrixtissue_scMappR_custom
Gene List Visualization and Enrichment (Internal)tissue_scMappR_internal
To Character.tochr
To Numeric.toNum
Extract Top Markerstopgenes_extract
two_method_pathway_enrichmenttwo_method_pathway_enrichment