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https://github.com/biogenies/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.
https://github.com/biogenies/cancergram
anticancer-peptides bioinformatics k-mer n-gram peptide-identification r-package random-forests
Last synced: about 1 month ago
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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.
- Host: GitHub
- URL: https://github.com/biogenies/cancergram
- Owner: BioGenies
- Created: 2020-10-01T14:57:04.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-11-19T20:31:32.000Z (about 4 years ago)
- Last Synced: 2024-10-28T17:32:33.884Z (2 months ago)
- Topics: anticancer-peptides, bioinformatics, k-mer, n-gram, peptide-identification, r-package, random-forests
- Language: R
- Homepage: https://biogenies.github.io/CancerGram/
- Size: 1.73 MB
- Stars: 4
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
[](https://doi.org/10.3390/pharmaceutics12111045)
[](https://github.com/BioGenies/CancerGram/actions)
[](https://cran.r-project.org/package=CancerGram)
[](https://cran.r-project.org/package=CancerGram)
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 <- read_txt(system.file("CancerGram/prots.txt", package = "CancerGram"))
predict(CancerGram_model, 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.