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Keywords from Contributors
Repository
Gene set scoring for single-cell data
Basic Info
Statistics
- Stars: 159
- Watchers: 4
- Forks: 19
- Open Issues: 8
- Releases: 10
Metadata Files
README.md
UCell: Robust and scalable single-cell gene signature scoring
UCell is an R package for scoring gene signatures in single-cell datasets. UCell scores, based on the Mann-Whitney U statistic, are robust to dataset size and heterogeneity, and their calculation demands relatively less computing time and memory than other robust methods, enabling the processing of large datasets (>10^5 cells). UCell can be applied to any cell vs. gene data matrix, and includes functions to directly interact with Seurat and Bioconductor's SingleCellExperiment objects.
Find the installation instructions for the package and usage vignettes below.
Package Installation
UCell is on Bioconductor To install the package from Bioc run:
r
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("UCell")
For previous releases of UCell, you may download a tagged version from GitHub:
r
library(remotes)
remotes::install_github("carmonalab/UCell", ref="v2.2")
Test the package
Load sample data and test your installation: ```r library(UCell)
data(sample.matrix) gene.sets <- list(Tcellsignature = c("CD2","CD3E","CD3D"), Myeloidsignature = c("SPI1","FCER1G","CSF1R"))
scores <- ScoreSignatures_UCell(sample.matrix, features=gene.sets) head(scores) ```
Vignettes and examples
Vignettes to run UCell on matrices, SingleCellExperiment or Seurat objects can be found at the UCell Bioc page.
Extended tutorial are also available at:
New in version >= 2.7.6
Calculation of UCell scores has been updated as follows:
${UCell} = 1 - {U} / {U_{max}}$
where
$U = \sum{i} r{i} - s_{min}$
$U{max} = s{max} - s_{min}$
$s_{max} = n * {maxRank}$
$s_{min} = n(n+1) / 2$
$n$ is the number of genes in the signature, ${maxRank}$ is a parameter limiting the ranking to the top genes, and U is the Mann-Whitney U statistic (bounded by 0 and $U{max}$). Earlier implementations used $U{max} = s_{max}$ to normalize the U statistics. While for typical applications results should be similar between the two implementations, the new normalization provides more homogeneous UCell score distributions for large gene sets.
New in version >= 2.1.2
Single-cell data are sparse. It can be useful to 'impute' scores by neighboring cells and partially correct this sparsity. The new function SmoothKNN performs smoothing of single-cell signature scores by weighted average of the k-nearest neighbors in a given dimensionality reduction. It can be applied directly on SingleCellExperiment or Seurat objects to smooth UCell scores:
r
obj <- SmoothKNN(obj, signature.names = sigs, reduction="pca")
Interacting with signatures
For easy retrieval and storing of signatures, check out SignatuR:
```r remotes::install_github("carmonalab/SignatuR") library(SignatuR)
e.g. get a cycling signature
cycling.G1S <- GetSignature(SignatuR$Hs$Programs$cellCycle.G1S) ```
Note that UCell supports positive and negative gene sets within a signature. Simply append + or - signs to the genes to include them in positive and negative sets, respectively. For example:
r
my_signature <- c("CD2+","CD8A+","CD4-")
Get help
See more information about UCell and its functions by typing ?UCell within R. Please address your questions and bug reports at: UCell issues.
Citation
UCell: robust and scalable single-cell gene signature scoring. Massimo Andreatta & Santiago J Carmona (2021) CSBJ https://doi.org/10.1016/j.csbj.2021.06.043
Owner
- Name: Cancer Systems Immunology Lab
- Login: carmonalab
- Kind: organization
- Location: Lausanne, Switzerland
- Website: https://agora-cancer.ch/laboratory/carmona-lab
- Twitter: carmonation
- Repositories: 16
- Profile: https://github.com/carmonalab
At Ludwig Cancer Research Lausanne and Department of Oncology, University of Lausanne & Swiss Institute of Bioinformatics
GitHub Events
Total
- Create event: 3
- Issues event: 12
- Release event: 2
- Watch event: 20
- Issue comment event: 16
- Push event: 13
- Fork event: 5
Last Year
- Create event: 3
- Issues event: 12
- Release event: 2
- Watch event: 20
- Issue comment event: 16
- Push event: 13
- Fork event: 5
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Massimo Andreatta | m****a@u****h | 71 |
| Santiago Carmona | s****a@g****m | 10 |
| Massimo Andreatta | 5****a | 9 |
| J Wokaty | j****y@s****u | 4 |
| Santiago Carmona | s****a@u****h | 3 |
| Nitesh Turaga | n****a@g****m | 2 |
| J Wokaty | j****y | 2 |
| HyacinthViolet | r****n@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 48
- Total pull requests: 1
- Average time to close issues: about 2 months
- Average time to close pull requests: about 4 hours
- Total issue authors: 41
- Total pull request authors: 1
- Average comments per issue: 2.27
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 9
- Pull requests: 0
- Average time to close issues: about 2 hours
- Average time to close pull requests: N/A
- Issue authors: 8
- Pull request authors: 0
- Average comments per issue: 0.56
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ksaunders73 (5)
- alexwskh (2)
- jcshuy (2)
- elifozcelik (1)
- hongjianjin (1)
- JLTrincado (1)
- amjass12 (1)
- ncedi12 (1)
- ozcelikelif (1)
- chvandijk (1)
- joachimsiaw (1)
- yeroslaviz (1)
- bhyu0217 (1)
- wodanaz (1)
- deevdevil88 (1)
Pull Request Authors
- RuiyuRayWang (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- bioconductor 68,918 total
- Total dependent packages: 1
- Total dependent repositories: 0
- Total versions: 7
- Total maintainers: 1
bioconductor.org: UCell
Rank-based signature enrichment analysis for single-cell data
- Homepage: https://github.com/carmonalab/UCell
- Documentation: https://bioconductor.org/packages/release/bioc/vignettes/UCell/inst/doc/UCell.pdf
- License: GPL-3 + file LICENSE
-
Latest release: 2.12.0
published 11 months ago
Rankings
Maintainers (1)
Dependencies
- R >= 4.2.0 depends
- BiocNeighbors * imports
- BiocParallel * imports
- Matrix * imports
- SingleCellExperiment * imports
- SummarizedExperiment * imports
- data.table >= 1.13.6 imports
- methods * imports
- BiocStyle * suggests
- Seurat * suggests
- ggplot2 * suggests
- knitr * suggests
- patchwork * suggests
- reshape2 * suggests
- rmarkdown * suggests
- scRNAseq * suggests
- scater * suggests