scLANE
Model Gene Expression Dynamics with Spline-Based NB GLMs, GEEs, & GLMMs
Bioconductor version: 3.23 · Package version: 1.2.0
Our scLANE model uses truncated power basis spline models to build flexible, interpretable models of single cell gene expression over pseudotime or latent time. The modeling architectures currently supported are Negative-binomial GLMs, GEEs, & GLMMs. Downstream analysis functionalities include model comparison, dynamic gene clustering, smoothed counts generation, gene set enrichment testing, & visualization.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scLANE") Details
| Maintainer | Jack R. Leary <j.leary@ufl.edu> |
| Author | Jack R. Leary [aut, cre] (ORCID: <https://orcid.org/0009-0004-8821-3269>), Rhonda Bacher [ctb, fnd] (ORCID: <https://orcid.org/0000-0001-5787-476X>) |
| License | MIT + file LICENSE |
| URL | https://github.com/jr-leary7/scLANE |
| Bug Reports | https://github.com/jr-leary7/scLANE/issues |
| Downloads rank | 127 |
| Source branch | RELEASE_3_23 |
| biocViews | Clustering, DifferentialExpression, GeneExpression, GeneSetEnrichment, RNASeq, Regression, Sequencing, SingleCell, Software, TimeCourse, Transcriptomics, Visualization |
Documentation
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Dependencies
Depends: glm2, magrittr, R (>= 4.5.0)
Imports: geeM, MASS, mpath, dplyr, stats, utils, withr, purrr, tidyr, furrr, doSNOW, gamlss, scales, future, Matrix, ggplot2, splines, foreach, glmmTMB, parallel, RcppEigen, bigstatsr, tidyselect, broom.mixed, Rcpp
Suggests: covr, grid, coop, uwot, scran, ggh4x, knitr, UCell, irlba, rlang, magick, igraph, scater, gtable, ggpubr, viridis, bluster, cluster, circlize, speedglm, rmarkdown, gridExtra, BiocStyle, slingshot, gprofiler2, GenomeInfoDb, BiocParallel, BiocGenerics, BiocNeighbors, ComplexHeatmap, Seurat (>= 5.0.0), testthat (>= 3.0.0), SingleCellExperiment, SummarizedExperiment