CancerGram
Predicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI.
Science Score: 13.0%
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 4 DOI reference(s) in README -
○Academic publication links
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○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 (14.3%) to scientific vocabulary
Keywords
Repository
Predicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI.
Basic Info
- Host: GitHub
- Owner: BioGenies
- Language: R
- Default Branch: master
- Homepage: https://biogenies.github.io/CancerGram/
- Size: 1.73 MB
Statistics
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
Identify anticancer peptides
CancerGram identifies anticancer peptides using n-gram encoding and random forests. It can be also accessed as a web-based service http://biongram.biotech.uni.wroc.pl/CancerGram/.
How to cite?
Please use: Burdukiewicz, M., Sidorczuk, K., Rafacz, D., Pietluch, F., Bąkała, M., Słowik, J., and Gagat, P. (2020). CancerGram: An Effective Classifier for Differentiating Anticancer from Antimicrobial Peptides. Pharmaceutics 12, 1045, https://doi.org/10.3390/pharmaceutics12111045.
Local instance of CancerGram
You can install the latest development version of the package:
R
source("https://raw.githubusercontent.com/r-lib/remotes/master/install-github.R")$value("BioGenies/CancerGram")
After installation GUI can be accessed locally:
R
library(CancerGram)
CancerGram_gui()
Installing dependency: CancerGramModel
To be able to use CancerGram properly, you should have installed the 'CancerGramModel' package available via GitHub. CancerGramModel contains stacked random forest model and informative n-grams required for prediction of anticancer peptides. Due to the large size of a model, it needs to be stored in the external repository, as CRAN do not allow upload of files larger than 5 MB.
You can install CancerGramModel using the install_CancerGramModel function:
R
install_CancerGramModel()
Anticancer peptides might be also identified in the batch mode:
```R library(CancerGram) library(CancerGramModel)
if you do not have CancerGramModel use:
install_CancerGramModel()
sequences <- readtxt(system.file("CancerGram/prots.txt", package = "CancerGram")) predict(CancerGrammodel, sequences) ```
Unix/macOS: curl
The curl library is one of the dependencies of the CancerGram package and requires additional, non-R software. If you encounter an error concerning curl, please follow instructions below to install curl (adapted from https://github.com/jeroen/curl).
Binary packages for OS-X or Windows can be installed directly from CRAN:
r
install.packages("curl")
Installation from source on Linux requires libcurl. On Debian or Ubuntu use libcurl4-openssl-dev:
bash
sudo apt-get install -y libcurl-dev
On Fedora, CentOS or RHEL use libcurl-devel:
bash
sudo yum install libcurl-devel
On OS-X libcurl is included with the system so nothing extra is needed. However if you want to build against the most recent version of libcurl, install and force-link curl from homebrew:
bash
brew install curl
brew link --force curl
Note that on OS-X you must recompile the R package from source after force-linking curl, otherwise you get a version conflict with the system version of libcurl.
Funding
This work was supported by National Science Centre grants 2017/26/D/NZ8/00444, 2018/31/N/NZ2/01338 and 2019/35/N/NZ8/03366 to FP.
Owner
- Name: BioGenies
- Login: BioGenies
- Kind: organization
- Repositories: 16
- Profile: https://github.com/BioGenies
GitHub Events
Total
Last Year
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Michał Burdukiewicz | m****z@g****m | 22 |
| Filip Pietluch | f****h@g****m | 12 |
| ksidorczuk | s****7@g****m | 11 |
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
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Packages
- Total packages: 1
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Total downloads:
- cran 246 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 1
- Total maintainers: 1
cran.r-project.org: CancerGram
Prediction of Anticancer Peptides
- Homepage: https://github.com/BioGenies/CancerGram
- Documentation: http://cran.r-project.org/web/packages/CancerGram/CancerGram.pdf
- License: GPL-3
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Latest release: 1.0.0
published over 5 years ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.5.0 depends
- biogram * imports
- devtools * imports
- dplyr * imports
- pbapply * imports
- ranger * imports
- shiny * imports
- stringi * imports
- DT * suggests
- ggplot2 * suggests
- pander * suggests
- rmarkdown * suggests
- shinythemes * suggests
- spelling * suggests