The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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>.

Version: 1.0.11
Depends: R (≥ 4.0.0)
Imports: ggplot2, pheatmap, graphics, Seurat, GSVA, stats, utils, downloader, pcaMethods, grDevices, gProfileR, limSolve, gprofiler2, pbapply, ADAPTS, reshape
Suggests: testthat, knitr, rmarkdown
Published: 2023-06-30
DOI: 10.32614/CRAN.package.scMappR
Author: 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]
Maintainer: Dustin Sokolowski <djsokolowski95 at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: scMappR results

Documentation:

Reference manual: scMappR.pdf
Vignettes: single cell Mapper (scMappR)

Downloads:

Package source: scMappR_1.0.11.tar.gz
Windows binaries: r-devel: scMappR_1.0.11.zip, r-release: scMappR_1.0.11.zip, r-oldrel: scMappR_1.0.11.zip
macOS binaries: r-release (arm64): scMappR_1.0.11.tgz, r-oldrel (arm64): not available, r-release (x86_64): scMappR_1.0.11.tgz, r-oldrel (x86_64): not available
Old sources: scMappR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=scMappR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.