dominoSignal
A software package for connecting cell level features in single cell RNA sequencing data with receptor ligand activity.
Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
○codemeta.json file
-
○.zenodo.json file
-
✓DOI references
Found 3 DOI reference(s) in README -
○Academic publication links
-
✓Committers with academic emails
5 of 18 committers (27.8%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (14.7%) to scientific vocabulary
Keywords from Contributors
Repository
A software package for connecting cell level features in single cell RNA sequencing data with receptor ligand activity.
Basic Info
- Host: GitHub
- Owner: FertigLab
- License: gpl-3.0
- Language: R
- Default Branch: master
- Homepage: https://fertiglab.github.io/dominoSignal/
- Size: 97.4 MB
Statistics
- Stars: 6
- Watchers: 1
- Forks: 4
- Open Issues: 9
- Releases: 0
Metadata Files
README.md
Introducing dominoSignal: Improved Inference of Cell Signaling from Single Cell RNA Sequencing Data 
dominoSignal is an updated version of the original domino R package published in Nature Biomedical Engineering in Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics. dominoSignal is a tool for analysis of intra- and intercellular signaling in single cell RNA sequencing data based on transcription factor activation and receptor and ligand linkages between clusters.
Installation
dominoSignal is the continuation of Domino software hosted on the Elisseeff-Lab GitHub. dominoSignal is undergoing active development where aspects of how data is used, analyzed, and interpreted is subject to change as new features and fixes are implemented. The most up to date stable version is on the FertigLab GitHub. This version of dominoSignal can be installed using the remotes package.
r
if(!require(remotes)){
install.packages('remotes')
}
remotes::install_github('FertigLab/dominoSignal')
Usage Overview
Here is an overview of how dominoSignal might be used in analysis of a single cell RNA sequencing data set:
- Transcription factor activation scores are calculated (we recommend using pySCENIC, but other methods can be used as well)
- A ligand-receptor database is used to map linkages between ligands and receptors (we recommend using CellPhoneDB, but other methods can be used as well).
- A domino object is created using counts, z-scored counts, clustering information, and the data from steps 1 and 2.
- Parameters such as the maximum number of transcription factors and receptors or the minimum correlation threshold (among others) are used to make a cell communication network
- Communication networks can be extracted from within the domino object or visualized using a variety of plotting functions
Please see our website for tutorials on all of these steps, from downloading and running pySCENIC in the SCENIC tutorial to building and visualizing domino results on the Getting Started page. Other articles include further details on plotting functions and the structure of the domino object.
Citation
If you use our package in your analysis, please cite us:
Cherry C, Maestas DR, Han J, Andorko JI, Cahan P, Fertig EJ, Garmire LX, Elisseeff JH. Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics. Nat Biomed Eng. 2021 Oct;5(10):1228-1238. doi: 10.1038/s41551-021-00770-5. Epub 2021 Aug 2. PMID: 34341534; PMCID: PMC9894531.
Cherry C, Mitchell J, Nagaraj S, Krishnan K, Lvovs D, Fertig E, Elisseeff J (2024). dominoSignal: Cell Communication Analysis for Single Cell RNA Sequencing. R package version 0.99.2.
Contact Us
If you find any bugs or have questions, please let us know here. tat
Owner
- Name: FertigLab
- Login: FertigLab
- Kind: organization
- Email: ejfertig@jhmi.edu
- Repositories: 68
- Profile: https://github.com/FertigLab
Software projects in computational biology and bioinformatics in Elana Fertig's lab in Oncology Biostatistics and Bioinformatics at JHMI
GitHub Events
Total
- Create event: 11
- Release event: 1
- Issues event: 16
- Watch event: 2
- Delete event: 4
- Issue comment event: 12
- Push event: 58
- Pull request review event: 13
- Pull request review comment event: 7
- Pull request event: 18
- Fork event: 1
Last Year
- Create event: 11
- Release event: 1
- Issues event: 16
- Watch event: 2
- Delete event: 4
- Issue comment event: 12
- Push event: 58
- Pull request review event: 13
- Pull request review comment event: 7
- Pull request event: 18
- Fork event: 1
Committers
Last synced: 11 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Jacob Mitchell | j****1@j****u | 288 |
| dimalvovs | d****s@g****m | 81 |
| kjkrishnan | k****2@j****u | 78 |
| dimalvovs | d****1@j****u | 27 |
| Chris-Cherry | c****4@g****m | 18 |
| Chris-Cherry | 3****y@u****m | 11 |
| jmitchell81 | j****1@u****m | 10 |
| kjkrishnan | 6****n@u****m | 7 |
| Jacob Mitchell | 8****1@u****m | 5 |
| kjkrishnan | k****n@u****m | 5 |
| Sushma Nagaraj | s****j@e****u | 3 |
| Sushma Nagaraj | s****j@e****m | 2 |
| dimalvovs | d****s@u****m | 2 |
| theron-palmer | t****m@g****m | 2 |
| GitHub Action | a****n@g****m | 1 |
| J Wokaty | j****y@s****u | 1 |
| Sushma Nagaraj | s****j@E****l | 1 |
| snagara5 | s****5@E****l | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 3
- Total pull requests: 3
- Average time to close issues: 24 days
- Average time to close pull requests: 1 day
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 3
- Average time to close issues: 24 days
- Average time to close pull requests: 1 day
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- dimalvovs (9)
- jmitchell81 (6)
- kjkrishnan (4)
- bryan-mccarty (1)
- mindykimgraham (1)
Pull Request Authors
- jmitchell81 (14)
- kjkrishnan (6)
- dimalvovs (4)
- snag-gh (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- bioconductor 2,252 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
bioconductor.org: dominoSignal
Cell Communication Analysis for Single Cell RNA Sequencing
- Homepage: https://fertiglab.github.io/dominoSignal/
- Documentation: https://bioconductor.org/packages/release/bioc/vignettes/dominoSignal/inst/doc/dominoSignal.pdf
- License: GPL-3 | file LICENSE
-
Latest release: 1.2.0
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.6.2 depends
- ComplexHeatmap * imports
- biomaRt * imports
- circlize * imports
- dplyr * imports
- igraph * imports
- plyr * imports