Ibex
Methods for BCR single-cell embedding
Bioconductor version: 3.24 · Package version: 1.3.1
Implementation of the Ibex algorithm for single-cell embedding based on BCR sequences. The package includes a standalone function to encode BCR sequence information by amino acid properties or sequence order using tensorflow-based autoencoder. In addition, the package interacts with SingleCellExperiment or Seurat data objects.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Ibex")Details
| Maintainer | Nick Borcherding <ncborch@gmail.com> |
| Author | Nick Borcherding [aut, cre, cph], Qile Yang [ctb] (ORCID: <https://orcid.org/0009-0005-0148-2499>) |
| License | MIT + file LICENSE |
| URL | https://github.com/BorchLab/Ibex/ |
| Bug Reports | https://github.com/BorchLab/Ibex/issues |
| System Requirements | Python (via basilisk) |
| Downloads rank | 244 |
| Source branch | devel |
| biocViews | Annotation, Classification, ImmunoOncology, Sequencing, SingleCell, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | Ibex_1.3.1.tar.gz |
| macOS binary (arm64) | Ibex_1.3.1.tgz |
| macOS binary (x86_64) | Ibex_1.3.1.tgz |
Dependencies
Depends: R (>= 4.5.0)
Imports: basilisk, immApex (>= 1.3.2), methods, Matrix, reticulate (>= 1.43.0), SeuratObject, scRepertoire, SingleCellExperiment, stats, SummarizedExperiment, tensorflow, tools
Suggests: basilisk.utils, BiocStyle, bluster, dplyr, ggplot2, kableExtra, knitr, lifecycle, markdown, mumosa, patchwork, Peptides, rmarkdown, scater, spelling, testthat (>= 3.0.0), utils, viridis