singscore
An R/Bioconductor package that implements a single-sample molecular phenotyping approach
Science Score: 23.0%
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Found 6 DOI reference(s) in README -
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Repository
An R/Bioconductor package that implements a single-sample molecular phenotyping approach
Basic Info
- Host: GitHub
- Owner: DavisLaboratory
- Language: R
- Default Branch: master
- Homepage: https://davislaboratory.github.io/singscore/
- Size: 18.1 MB
Statistics
- Stars: 45
- Watchers: 8
- Forks: 5
- Open Issues: 4
- Releases: 0
Topics
Metadata Files
README.md
singscore 
Overview
‘singscore’ is an R/Bioconductor package which implements the simple single-sample gene-set (or gene-signature) scoring method proposed by Foroutan et al. (2018) and Bhuva et al. (2020). It uses rank-based statistics to analyze each sample’s gene expression profile and scores the expression activities of gene sets at a single-sample level.
Additional packages we have developed can enhance the singscore workflow:
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msigdb- A package that provides gene-sets from the molecular signatures database (MSigDB) as aGeneSetCollectionobject that is compatible withsingscore. -
vissE- A package that can summarise and aid in the interpretation of a list of significant gene-sets identified bysingscore(see tutorial). -
emtdata- The full EMT dataset used in this tutorial (with additional EMT related datasets).
We have also published and made openly available the extensive tutorials
below that demonstrate the variety of ways in which singscore can be
used to gain a better functional understanding of molecular data:
- Using singscore to predict mutation status in acute myeloid leukemia from transcriptomic signatures.
- Gene-set enrichment analysis workshop - available through the Orchestra platform (search “WEHI Masterclass Day 4: Functional Analysis, single sample gene set analysis”).
Getting Started
These instructions will get you to install the package up and running on your local machine. If you experience any issues, please raise a GitHub issue at https://github.com/DavisLaboratory/singscore/issues.
# build_vignettes = TRUE to build vignettes upon installation
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("singscore", version = "3.8")
Documentation
The package comes with a vignette showing how the different functions in the package can be used to perform a gene-set enrichment analysis on a single sample level. Pre-built vignettes can be accessed via Bioconductor or the GitHub IO page.
References
Foroutan M, Bhuva D, Lyu R, Horan K, Cursons J, Davis M (2018). “Single sample scoring of molecular phenotypes.” BMC bioinformatics, 19(1), 404. doi: 10.1186/s12859-018-2435-4.
Bhuva D, Cursons J, Davis M (2020). “Stable gene expression for normalisation and single-sample scoring.” Nucleic Acids Research, 48(19), e113. doi: 10.1093/nar/gkaa802.
Owner
- Name: Davis Laboratory
- Login: DavisLaboratory
- Kind: organization
- Location: Melbourne, Australia
- Website: http://www.wehi.edu.au/people/melissa-davis
- Repositories: 18
- Profile: https://github.com/DavisLaboratory
computational systems biology of cancer
GitHub Events
Total
- Issues event: 1
- Watch event: 5
- Issue comment event: 4
- Push event: 1
- Fork event: 1
Last Year
- Issues event: 1
- Watch event: 5
- Issue comment event: 4
- Push event: 1
- Fork event: 1
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| bhuvad | b****d@w****u | 70 |
| Ruqian Lyu | x****t@g****m | 44 |
| Nitesh Turaga | n****a@g****m | 14 |
| Ruqian Lyu | r****u@R****l | 7 |
| Dharmesh Bhuva | d****a@a****u | 5 |
| J Wokaty | j****y@s****u | 2 |
| Ruqian Lyu | r****u@u****u | 2 |
| vobencha | v****n@r****g | 2 |
| vobencha | v****a@g****m | 2 |
| Ahmed Mohamed | a****0@g****m | 1 |
| Hervé Pagès | h****b@g****m | 1 |
| LiNk-NY | m****9@g****m | 1 |
| Ruqian Lyu | r****u@u****u | 1 |
Committer Domains (Top 20 + Academic)
Packages
- Total packages: 1
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Total downloads:
- bioconductor 101,144 total
- Total dependent packages: 3
- Total dependent repositories: 0
- Total versions: 5
- Total maintainers: 1
bioconductor.org: singscore
Rank-based single-sample gene set scoring method
- Homepage: https://davislaboratory.github.io/singscore
- Documentation: https://bioconductor.org/packages/release/bioc/vignettes/singscore/inst/doc/singscore.pdf
- License: GPL-3
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Latest release: 1.28.0
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.6 depends
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