KeBABS - An R Package for Kernel-Based Analysis of Biological Sequences
The kebabs package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.Installation
The R package kebabs is available from Bioconductor. The first version of the package has been released as part of Bioconductor 3.0 on October 14, 2014. The current release version is 1.20.0 (released on October 30, 2019, as part of Bioconductor 3.10). To install kebabs, follow the simple standard procedure for installing Bioconductor packages, i.e. enter the following into your R session:Please note that Bioconductor 3.10 requires R version 3.6.1.if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("kebabs")
The current development version of the package is 1.21.0.
Documentation
Getting started
- To load the package, enter "library(kebabs)" in your R session.
- To view the user manual, enter "vignette("kebabs")".
- To do a first example, enter "example(kebabs)".
User support
If you encounter any issues or if you have any question that might be of interest also for other users, before writing a private message to the package developers/maintainers, please consider posting on Bioconductor Support or StackOverflow. For all other matters regarding the package, please contact kebabs@bioinf.jku.at.Citing this package
If you use this package for research that is published later, you are kindly asked to cite it as follows:J. Palme, S. Hochreiter, and U. Bodenhofer (2015). KeBABS: an R package for kernel-based analysis of biological sequences. Bioinformatics 31(15):2574-2576. DOI: 10.1093/bioinformatics/btv176.
R source code for example on epitope-to-MHC binding: A0201-Example.zip (3.7 KB; see file README.txt for more information)