doi:10.1093/bioinformatics/bty256>) and specialized tools for downstream analyses. 'grandR' provides a comprehensive toolbox for quality control, kinetic modeling, differential gene expression analysis and visualization of such data.">

grandR: Comprehensive Analysis of Nucleotide Conversion Sequencing Data (original) (raw)

Nucleotide conversion sequencing experiments have been developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such experiments require specialized tools for primary processing such as GRAND-SLAM, (see 'Jürges et al' <doi:10.1093/bioinformatics/bty256>) and specialized tools for downstream analyses. 'grandR' provides a comprehensive toolbox for quality control, kinetic modeling, differential gene expression analysis and visualization of such data.

Version: 0.2.5
Depends: R (≥ 3.5.0)
Imports: stats, Matrix, rlang, ggplot2, grDevices, patchwork, RCurl, plyr, parallel, reshape2, MASS, scales, cowplot, minpack.lm, lfc, labeling, methods, utils, numDeriv
Suggests: knitr, rmarkdown, circlize, Seurat, ComplexHeatmap, ggrepel, DESeq2, S4Vectors, data.table, clusterProfiler, biomaRt, msigdbr, fgsea, rclipboard, cubature, DT, shinyjs, shinyjqui, RColorBrewer, gsl, htmltools, matrixStats, monocle, VGAM, quantreg, graphics, shiny, ggrastr, viridisLite, deSolve
Published: 2024-02-15
DOI: 10.32614/CRAN.package.grandR
Author: Florian Erhard ORCID iD [aut, cre], Teresa Rummel [ctb], Lygeri Sakellaridi [ctb], Kevin Berg [ctb]
Maintainer: Florian Erhard <Florian.Erhard at informatik.uni-regensburg.de>
BugReports: https://github.com/erhard-lab/grandR/issues
License: Apache License (≥ 2)
URL: https://github.com/erhard-lab/grandR
NeedsCompilation: yes
Citation: grandR citation info
Materials: README NEWS
CRAN checks: grandR results

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