https://github.com/bioconductor-source/scdd
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.0%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: bioconductor-source
- Language: R
- Default Branch: devel
- Size: 10.2 MB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
scDD: An R package to identify differentially distributed genes in scRNA-seq
Installation
The Bioconductor landing page is https://bioconductor.org/packages/scDD. To install, make sure you have the current version of Bioconductor, and use the following commands:
R
install.packages("BiocManager")
BiocManager::install("scDD")
Quick Start
For examples and tips on using the package, please see the vignette PDF here which you can alternatively bring up by typing
R
browseVignettes("scDD")
after installing and loading the package into R.
Getting Help
Please send bug reports and feature requests by sending a message to Bioconductor Support at https://support.bioconductor.org or by opening a new issue on this page
Citation
Please cite the following publication if you use scDD in your work:
Korthauer KD, Chu LF, Newton MA, Li Y, Thomson J, Stewart R, Kendziorski C. A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Genome Biology. 2016 Oct 25;17(1):222. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1077-y
You can obtain this citation within R by typing
R
citation("scDD")
Owner
- Name: (WIP DEV) Bioconductor Packages
- Login: bioconductor-source
- Kind: organization
- Email: maintainer@bioconductor.org
- Website: https://bioconductor.org
- Repositories: 1
- Profile: https://github.com/bioconductor-source
Source code for packages accepted into Bioconductor
GitHub Events
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Last Year
Dependencies
- R >= 3.4 depends
- BiocParallel * imports
- EBSeq * imports
- S4Vectors * imports
- SingleCellExperiment * imports
- SummarizedExperiment * imports
- arm * imports
- fields * imports
- ggplot2 * imports
- grDevices * imports
- graphics * imports
- mclust * imports
- outliers * imports
- scran * imports
- stats * imports
- BiocStyle * suggests
- gridExtra * suggests
- knitr * suggests