KeBABS - An R Package for Kernel-Based Analysis of Biological Sequences
This is a legacy page. The package is now hosted on GitHub.
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. Therefore, the the simplest way to install the package is to enter
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("kebabs")
into your R session. If, for what reason ever, you prefer to install the package manually, follow the instructions in the user manual.
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 create an issue in the source code repository and also consider posting on Bioconductor Support or StackOverflow.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)