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README.md
In escape: Easy single cell analysis platform for enrichment
escape
Easy single cell analysis platform for enrichment
Introduction
Single-cell sequencing (SCS) is an emerging technology in the across the diverse array of biological fields. Part of the struggle with the high-resolution approach of SCS, is distilling the data down to meaningful scientific hypotheses. escape was created to bridge SCS results, either from raw counts or from the popular Seurat R package, with gene set enrichment analyses (GSEA), allowing users to simply and easily graph outputs. The package accesses the entire Molecular Signature Database v7.0 and enables users to select single, multiple gene sets, and even libraries to perform enrichment analysis on.
R Packages Imported
- dplyr
- facoextra
devtools::install_github("kassambara/factoextra")
- ggplots2
- ggrepel
- ggridges
- grDevices
- GSEABase
- GSVA
- msigdbr
- limma
- pheatmap
- rlang
- Seurat
- SingleCellExperiment
Installation
devtools::install_github("ncborcherding/escape")
Learning To Use escape:
Vignette available here, includes 2,000 malignant and nonmalignant peripheral blood T cells from a patient with cutaenous T cell lymphoma.
Contact
Questions, comments, suggestions, please feel free to contact Nick Borcherding via this repository, email, or using twitter.
Try the escape package in your browser
Any scripts or data that you put into this service are public.
escape documentation built on Nov. 8, 2020, 8:21 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
escape
Easy single cell analysis platform for enrichment
Introduction
Single-cell sequencing (SCS) is an emerging technology in the across the diverse array of biological fields. Part of the struggle with the high-resolution approach of SCS, is distilling the data down to meaningful scientific hypotheses. escape was created to bridge SCS results, either from raw counts or from the popular Seurat R package, with gene set enrichment analyses (GSEA), allowing users to simply and easily graph outputs. The package accesses the entire Molecular Signature Database v7.0 and enables users to select single, multiple gene sets, and even libraries to perform enrichment analysis on.
R Packages Imported
- dplyr
- facoextra
devtools::install_github("kassambara/factoextra") - ggplots2
- ggrepel
- ggridges
- grDevices
- GSEABase
- GSVA
- msigdbr
- limma
- pheatmap
- rlang
- Seurat
- SingleCellExperiment
Installation
devtools::install_github("ncborcherding/escape")
Learning To Use escape:
Vignette available here, includes 2,000 malignant and nonmalignant peripheral blood T cells from a patient with cutaenous T cell lymphoma.
Contact
Questions, comments, suggestions, please feel free to contact Nick Borcherding via this repository, email, or using twitter.
Try the escape package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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