ILoReg
A tool for high-resolution cell population identification from single-cell RNA-seq data
Science Score: 13.0%
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Low similarity (11.8%) to scientific vocabulary
Repository
A tool for high-resolution cell population identification from single-cell RNA-seq data
Basic Info
- Host: GitHub
- Owner: elolab
- Language: R
- Default Branch: master
- Size: 15.5 MB
Statistics
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
ILoReg
Introduction
ILoReg is a novel tool for cell population identification from single-cell RNA-seq (scRNA-seq) data. In our study [1], we showed that ILoReg was able to identify, by both unsupervised clustering and visually, rare cell populations that other scRNA-seq data analysis pipelines were unable to identify.
The figure below illustrates the workflows of ILoReg and a typical pipeline that applies feature selection prior to dimensionality reduction by principal component analysis (PCA).
In contrast to most scRNA-seq data analysis pipelines, ILoReg does not reduce the dimensionality of the gene expression matrix by feature selection. Instead, it performs probabilistic feature extraction using iterative clustering projection (ICP), yielding a probability matrix, which contains probabilities of each of the N cells belonging to the k clusters. ICP is a novel machine learning algorithm that iteratively seeks a clustering with k clusters that maximizes the adjusted Rand index (ARI) between the clustering and its projection by L1-regularized logistic regression. In the ILoReg consensus approach, ICP is run L times and the L probability matrices are merged into a joint probability matrix and subsequently transformed by principal component analysis (PCA) into a lower dimensional matrix (consensus matrix). The final clustering step is performed using hierarhical clustering by the Ward's method, after which the user can extract a clustering with K consensus clusters. Two-dimensional visualization is supported using two popular nonlinear dimensionality reduction methods: t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). Additionally, ILoReg provides user-friendly functions that enable identification of differentially expressed (DE) genes and visualization of gene expression.
Installation
The latest version of ILoReg can be downloaded from GitHub using the devtools R package.
```R
devtools::install_github("elolab/ILoReg")
```
Example
Please follow this link to an example, in which a peripheral blood mononuclear cell (PBMC) dataset is analyzed using ILoReg. In Bioconductor the vignette can be accessed in a readable format.
Contact information
If you have questions related to ILoReg, please contact us here.
References
- Johannes Smolander, Sini Junttila, Mikko S Venäläinen, Laura L Elo. " ILoReg: a tool for high-resolution cell population identification from single-cell RNA-seq data". Bioinformatics, Volume 37, Issue 8, 15 April 2021, Pages 1107–1114, https://doi.org/10.1093/bioinformatics/btaa919.
Owner
- Name: Elo Lab
- Login: elolab
- Kind: organization
- Location: Finland
- Website: https://elolab.utu.fi
- Repositories: 7
- Profile: https://github.com/elolab
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| Name | Commits | |
|---|---|---|
| Johannes Smolander | p****m@u****i | 88 |
| Johannes Smolander | j****r@u****i | 12 |
| Johannes Smolander | j****r@g****m | 6 |
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Last synced: 12 months ago
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Packages
- Total packages: 1
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Total downloads:
- bioconductor 7,789 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 6
- Total maintainers: 1
bioconductor.org: ILoReg
ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data
- Homepage: https://github.com/elolab/ILoReg
- Documentation: https://bioconductor.org/packages/release/bioc/vignettes/ILoReg/inst/doc/ILoReg.pdf
- License: GPL-3
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Latest release: 1.18.0
published about 1 year ago