immApex
Tools for Adaptive Immune Receptor Sequence-Based Machine and Deep Learning
Bioconductor version: 3.24 · Package version: 1.7.1
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
A set of tools to for machine and deep learning in R from amino acid and nucleotide sequences focusing on adaptive immune receptors. The package includes pre-processing of sequences, unifying gene nomenclature usage, encoding sequences, and combining models. This package will serve as the basis of future immune receptor sequence functions/packages/models compatible with the scRepertoire ecosystem.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("immApex")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/immApex/ |
| Bug Reports | https://github.com/BorchLab/immApex/issues |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Annotation, Classification, ImmunoOncology, MotifAnnotation, Sequencing, SingleCell, Software |
| Package Short Url | https://bioconductor.org/packages/immApex/ |
Citation
From within R, enter citation("immApex"):
Nick Borcherding. immApex: Tools for Adaptive Immune Receptor Sequence-Based Machine and Deep Learning. doi:10.18129/B9.bioc.immApex, R package version 1.7.1, https://bioconductor.org/packages/immApex.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | immApex_1.7.1.tar.gz |
| Windows binary (x86_64) | immApex_1.7.1.zip |
| macOS binary (arm64) | immApex_1.7.1.tgz |
| macOS binary (x86_64) | immApex_1.7.1.tgz |
Dependencies
Depends: R (>= 4.3.0)
Imports: immReferent, Matrix, matrixStats, methods, Rcpp, SingleCellExperiment, stats, stringr, utils
LinkingTo: Rcpp
Suggests: BiocStyle, dplyr, ggraph, ggplot2, igraph, knitr, markdown, Peptides, randomForest, rmarkdown, scRepertoire, spelling, testthat, tidygraph, viridis
Reverse dependencies
Imports Me (4): Ibex, immGLIPH, immLynx, scRepertoire