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scMappR
View on CRAN: Click
here
Download and install scMappR package within the R console
Install from CRAN:
install.packages("scMappR")
Install from Github:
library("remotes")
install_github("cran/scMappR")
Install by package version:
library("remotes")
install_version("scMappR", "1.0.11")
Attach the package and use:
library("scMappR")
Maintained by
Dustin Sokolowski
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.scMappR . scMappR results . scMappR.pdf . single cell Mapper (scMappR) . scMappR_1.0.11.tar.gz . scMappR_1.0.11.zip . scMappR_1.0.11.zip . scMappR_1.0.11.zip . scMappR_1.0.11.tgz . scMappR_1.0.11.tgz . scMappR_1.0.11.tgz . scMappR_1.0.11.tgz . scMappR archive . https://CRAN.R-project.org/package=scMappR .
First Published: 2020-03-04
Latest Update: 2023-06-30
Description:
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. .
How to cite:
Dustin Sokolowski (2020). scMappR: Single Cell Mapper. R package version 1.0.11, https://cran.r-project.org/web/packages/scMappR. Accessed 07 Apr. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for scMappR
Functions, R codes and Examples using
the scMappR R package
Some associated functions: DeconRNAseq_CRAN . PBMC_example . POA_example . cellmarker_enrich . coEnrich . compare_deconvolution_methods . cwFoldChange_evaluate . deconvolute_and_contextualize . extract_genes_cell . gProfiler_cellWeighted_Foldchange . generes_to_heatmap . get_gene_symbol . get_signature_matrices . gmt . gsva_cellIdentify . heatmap_generation . human_mouse_ct_marker_enrich . make_TF_barplot . pathway_enrich_internal . plotBP . process_dgTMatrix_lists . process_from_count . scMappR_and_pathway_analysis . scMappR_tissues . seurat_to_generes . single_gene_preferences . sm . tissue_by_celltype_enrichment . tissue_scMappR_custom . tissue_scMappR_internal . toNum . tochr . topgenes_extract . two_method_pathway_enrichment .
Some associated R codes: DeconRNAseq_CRAN.R . PBMC_example.R . POA_example.R . cellmarker_enrich.R . coEnrich.R . compare_deconvolution_methods.R . cwFoldChange_evaluate.R . deconvolute_and_contextualize.R . extract_genes_cell.R . gProfiler_cellWeighted_Foldchange.R . generes_to_heatmap.R . get_gene_symbol.R . get_signature_matrices.R . gmt.R . gsva_cellIdentify.R . heatmap_generation.R . human_mouse_ct_marker_enrich.R . make_TF_barplot.R . pathway_enrich_internal.R . plotBP.R . process_dgTMatrix_lists.R . process_from_count.R . scMappR_and_pathway_analysis.R . scMappR_tissues.R . seurat_to_generes.R . single_gene_preferences.R . sm.R . tissue_by_celltype_enirchment.R . tissue_scMappR_custom.R . tissue_scMappR_internal.R . toNum.R . tochr.R . topgenes_extract.R . two_method_pathway_enrichment.R . Full scMappR package functions and examples
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