https://github.com/bioconductor-source/scbfa
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
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○.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (3.9%) to scientific vocabulary
Last synced: 10 months ago
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JSON representation
Repository
Basic Info
- Host: GitHub
- Owner: bioconductor-source
- License: other
- Language: R
- Default Branch: devel
- Size: 4.4 MB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Created almost 2 years ago
· Last pushed almost 2 years ago
Metadata Files
Readme
Changelog
License
README.md
scBFA
Single cell Binary Factor Analysis (scBFA) and Binary PCA - These are tools for performing dimensionality reduction in large scRNA-seq datasets, as described in: Li, R., Quon, G. (2018) Gene detection models outperform gene expression for large-scale scRNA-seq analysis. bioRxiv doi: https://doi.org/10.1101/454629.
A user can install scBFA currently via the following command
library(devtools)\ install_github("quon-titative-biology/scBFA")
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
Dependencies
DESCRIPTION
cran
- R >= 3.6 depends
- DESeq2 * imports
- MASS * imports
- Matrix * imports
- Seurat * imports
- SingleCellExperiment * imports
- SummarizedExperiment * imports
- copula * imports
- ggplot2 * imports
- grid * imports
- methods * imports
- stats * imports
- utils * imports
- zinbwave * imports
- Rtsne * suggests
- knitr * suggests
- rmarkdown * suggests
- testthat * suggests