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 2 DOI reference(s) in README -
✓Academic publication links
Links to: ncbi.nlm.nih.gov -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.6%) to scientific vocabulary
Repository
Hierarchical classification of cells
Basic Info
- Host: GitHub
- Owner: SydneyBioX
- Language: R
- Default Branch: master
- Homepage: https://sydneybiox.github.io/scClassify/
- Size: 505 MB
Statistics
- Stars: 22
- Watchers: 10
- Forks: 5
- Open Issues: 10
- Releases: 0
Metadata Files
README.md
scClassify: hierarchical classification of cells
Single cell classification via cell-type hierarchies based on ensemble learning and sample size estimation.
Installation
Install Bioconductor packages S4Vectors, hopach and limma packages using BiocManager:
```r
install.packages("BiocManager")
BiocManager::install(c("S4Vectors", "hopach", "limma")) ```
Then install the latest scClassify using devtools (For R >= 4.0):
r
library(devtools)
devtools::install_github("SydneyBioX/scClassify")
For R >= 3.6, install scClassify(v0.2.3) via
devtools::install_github("SydneyBioX/scClassify@085c72f")
Vignette and Shiny app
You can find the vignette at this website (https://sydneybiox.github.io/scClassify/index.html):
- scClassify Model Building and Prediction: https://sydneybiox.github.io/scClassify/articles/scClassify.html
- Sample size calculation: https://sydneybiox.github.io/scClassify/articles/webOnly/sampleSizeCal.html
- Performing scClassify using pretrained models: https://sydneybiox.github.io/scClassify/articles/pretrainedModel.html
Also, you can find our interactive shiny application (beta) at this website: http://shiny.maths.usyd.edu.au/scClassify.
Pretrained models
Currently available pre-trained scClassify models (in scClassifyTrainModel class)
| Tissue | Organism | Training Data | Accession | Summary | Download .rds | Gene Name Format |
| :--: | :--: | :--: | :--: | :--: | :--: | :--: |
| Primary visual cortex | mouse | Tasic (2018) | GSE115746 | link| link | Mm Gene Symbol|
| Primary visual cortex | mouse | Tasic (2016) | GSE71585 | link| link | Mm Gene Symbol|
| Visual cortex | mouse | Hrvatin | GSE102827 | link | link | Mm Gene Symbol|
| Lung | mouse | Cohen | GSE119228 | link | link | Mm Gene Symbol|
| Kidney | mouse | Park | GSE107585 | link | link | Mm Gene Symbol|
| Liver | human | MacParland | GSE115469 | link | link | Hs Gene Symbol|
| Liver | human | Aizarani | GSE124395 | link | link | Hs Gene Symbol|
| Pancreas | human | Xin | GSE81608 | link | link | Hs Gene Symbol|
| Pancreas | human | Wang | GSE83139 | link | link | Hs Gene Symbol|
| Pancreas | human | Lawlor | GSE86469 | link | link | Hs Gene Symbol|
| Pancreas | human | Segerstolpe | E-MTAB-5061 | link | link | Hs Gene Symbol|
| Pancreas | human | Muraro | GSE85241 | link | link | Hs Gene Symbol|
| Pancreas | human | Baron | GSE84133 | link | link | Hs Gene Symbol|
| Pancreas | human | joint | - | link | link | Hs Gene Symbol|
| Melanoma | human | Li | GSE123139 | link | link | Hs Gene Symbol|
| PBMC | human | Ding (joint) | - | link | link | Mm EMSEMBL ID|
| Tabula Muris | mouse | Tabula Muris | GSE109774 | link | link | Mm Gene Symbol|
Contact us
If you have any enquiries, especially about performing scClassify to classify your cells or to build your own models, please contact yingxin.lin@sydney.edu.au or bioinformatics@maths.usyd.edu.au.
Reference
scClassify: sample size estimation and multiscale classification of cells using single and multiple reference
Yingxin Lin, Yue Cao, Hani Kim, Agus Salim, Terence Speed, David Lin, Pengyi Yang† & Jean Yang†. Molecular Systems Biology, 2020, 16, e9389. Full Text; BioC R package
Owner
- Name: Sydney Precision Data Science Centre
- Login: SydneyBioX
- Kind: organization
- Location: Sydney, Australia
- Website: https://www.sydney.edu.au/science/our-research/research-centres/sydney-precision-data-science-centre.html
- Twitter: sydneybioinfo
- Repositories: 76
- Profile: https://github.com/SydneyBioX
SPDSC alliance brings together multiple research groups and junior and senior researchers with shared interests in bioinformatics and computational sciences.
GitHub Events
Total
- Issues event: 1
- Watch event: 3
Last Year
- Issues event: 1
- Watch event: 3
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| yingxinlin | y****y@g****m | 41 |
| Nitesh Turaga | n****a@g****m | 6 |
| Pengyi Yang Laboratory | 1****b | 2 |
Dependencies
- R >= 4.0 depends
- BiocParallel * imports
- Cepo * imports
- Matrix * imports
- S4Vectors * imports
- cluster * imports
- diptest * imports
- ggplot2 * imports
- ggraph * imports
- graphics * imports
- hopach * imports
- igraph * imports
- limma * imports
- methods * imports
- mgcv * imports
- minpack.lm * imports
- mixtools * imports
- proxy * imports
- proxyC * imports
- statmod * imports
- stats * imports
- BiocStyle * suggests
- knitr * suggests
- pkgdown * suggests
- rmarkdown * suggests