Science Score: 23.0%
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 1 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
2 of 18 committers (11.1%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.6%) to scientific vocabulary
Keywords from Contributors
Repository
Tools and methods for analysis of single cell assay data in R
Basic Info
- Host: GitHub
- Owner: RGLab
- Language: R
- Default Branch: devel
- Size: 97.1 MB
Statistics
- Stars: 249
- Watchers: 9
- Forks: 57
- Open Issues: 38
- Releases: 3
Metadata Files
README.md
MAST: Model-based Analysis of Single-cell Transcriptomics
MAST fits two-part, generalized linear models that are specially adapted for bimodal and/or zero-inflated single cell gene expression data.
Examples and vignettes
MAST supports:
- Easy importing, subsetting and manipulation of expression matrices
- Filtering of low-quality cells
- Adaptive thresholding of background noise
- Tests for univariate differential expression, with adjustment for covariates
- Gene set enrichment analysis, corrected for covariates and gene-gene correlations
- Exploration of gene-gene correlations and co-expression
Vignettes are available in the package via vignette('MAITAnalysis'), vignette('MAST-Intro') or vignette('MAST-interoperability').
New Features and announcements
- MAST has been ported to use
SingleCellExperimentunder the hood, and is in Bioconductor. - We now make an effort to track assay contents (counts vs log counts). This should facilitate interaction with Scater and SCRAN.
Getting Help
For general questions, please submit a question to the bioconductor support site so that others can benefit from the discussion.
For bug reports (something seems broken): open a bug report here.
Installation Instructions
This version available here on github may only properly function if you are running Bioconductor Devel, which is not something you will want to run for existing analyses! Instead follow instructions below.
You may install or update MAST with:
install.packages("BiocManager") # Needed to install all Bioconductor packages
BiocManager::install("MAST")
Citation
If you find MAST useful in your work, please consider citing the paper: MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data G Finak, A McDavid, M Yajima, J Deng, V Gersuk, AK Shalek, CK Slichter et al Genome biology 16 (1), 278
The version that was used in the Genome Biology paper is accesible under the branch MASTClassic.
Converting old MASTClassic SingleCellAssay objects
If you have data analyzed using MASTClassic, you can convert
objects from MASTClassic format to the new format based on SingleCellExperiment using
convertMastClassicToSingleCellAssay().
Owner
- Name: RGLab
- Login: RGLab
- Kind: organization
- Location: Seattle
- Website: http://www.rglab.org/
- Repositories: 69
- Profile: https://github.com/RGLab
Raphael Gottardo's Research Lab
GitHub Events
Total
- Issues event: 4
- Watch event: 17
- Issue comment event: 4
Last Year
- Issues event: 4
- Watch event: 17
- Issue comment event: 4
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Andrew McDavid | a****d@g****m | 46 |
| Greg Finak | g****k@g****m | 35 |
| Andrew McDavid | a****d@f****g | 27 |
| Andrew McDavid | A****d@u****u | 27 |
| Nitesh Turaga | n****a@g****m | 18 |
| Greg Finak | g****k@f****g | 4 |
| Andrew McDavid | a****w@o****m | 4 |
| Herve Pages | h****s@f****g | 4 |
| Hervé Pagès | h****s@f****g | 3 |
| vobencha | v****a@g****m | 2 |
| Jacob Wagner | j****r@f****g | 2 |
| vobencha | v****n@r****g | 2 |
| J Wokaty | j****y@s****u | 2 |
| J Wokaty | j****y | 2 |
| Sean Hughes | s****n@g****m | 1 |
| Martin Morgan | m****n@f****g | 1 |
| Daniel Burkhardt | b****b@g****m | 1 |
| Derrik Gratz | 4****z | 1 |
Committer Domains (Top 20 + Academic)
Packages
- Total packages: 3
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Total downloads:
- bioconductor 211,128 total
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Total dependent packages: 6
(may contain duplicates) -
Total dependent repositories: 0
(may contain duplicates) - Total versions: 7
- Total maintainers: 1
bioconductor.org: MAST
Model-based Analysis of Single Cell Transcriptomics
- Homepage: https://github.com/RGLab/MAST/
- Documentation: https://bioconductor.org/packages/release/bioc/vignettes/MAST/inst/doc/MAST.pdf
- License: GPL(>= 2)
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Latest release: 1.33.0
published about 1 year ago
Rankings
Maintainers (1)
proxy.golang.org: github.com/RGLab/MAST
- Documentation: https://pkg.go.dev/github.com/RGLab/MAST#section-documentation
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Latest release: v1.0.1
published about 11 years ago
Rankings
proxy.golang.org: github.com/rglab/mast
- Documentation: https://pkg.go.dev/github.com/rglab/mast#section-documentation
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Latest release: v1.0.1
published about 11 years ago
Rankings
Dependencies
- R >= 3.5 depends
- SingleCellExperiment >= 1.2.0 depends
- Biobase * imports
- BiocGenerics * imports
- S4Vectors * imports
- SummarizedExperiment >= 1.5.3 imports
- abind * imports
- data.table * imports
- ggplot2 * imports
- graphics * imports
- methods * imports
- parallel * imports
- plyr * imports
- progress * imports
- reshape2 * imports
- stats * imports
- stats4 * imports
- stringr * imports
- utils * imports
- BiocStyle * suggests
- DelayedArray * suggests
- GGally * suggests
- GSEABase * suggests
- HDF5Array * suggests
- Matrix * suggests
- NMF * suggests
- RColorBrewer * suggests
- TxDb.Hsapiens.UCSC.hg19.knownGene * suggests
- blme * suggests
- car * suggests
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- lme4 >= 1.0 suggests
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